Effects of Opinion Polls and Media Reporting on Voters1
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Effects of Opinion Polls and Media Reporting on Voters1
A Multilevel Analysis
Hanna Hoffmann
Heinrich Heine University Düsseldorf
Department of Social Sciences
E-Mail: hanna.hoffmann@uni-duesseldorf.de
1. Introduction
Electoral researchers assume that the potential effects resulting from the effort put
into electoral campaigns by parties and media reporting are increasing. This can
mainly be attributed to individualisation processes, due to which political attitudes
lose their stability (Holtz-Bacha 2002). The main result of this instability is said to be
the decreasing number of long-term commitments to one of the well-established
parties (dealignment), which, among other things, causes voters to make their voting
decision later and later (Gallus 2002; Mc Allister 2002; Schmitt-Beck 2003; Irwin/Van
Holsteyn 2008; Neu 2008). This increased volatility on the part of the voters opens
the way to short-term effects. In addition to decreasing party affiliations, the more
professional nature of electoral campaigns promotes potential effects, since
campaigns are being used more strategically and efficiently to convince voters
(Schoen 2005).
The effects of opinion polls are often discussed in the context of possible influences
on voters prior to an election. Reporting has been gaining more and more importance
in political media coverage about electoral campaigns over the past years. Due to the
rising number of published opinion polls, it can be assumed that the population
increasingly knows about the results of polls (Brettschneider 1991), which leads to
increased potential effects. Despite the fact that many experts have made
assumptions regarding these effects, there are only very few empirical findings; in
addition, the methodical approaches of the analyses vary strongly.
This paper analyses the effects of published opinion polls on voters prior to the
parliamentary elections in Germany in 2009. The data provided by the rolling cross-
section study, which was completed in the context of the German Longitudinal
Election Study (GLES), is used for this analysis. The multilevel analysis is regarded
to be the best-suited analysis method here; it makes it possible to operationalise the
poll results and the corresponding media coverage as information context.
2. Theoretical expectations
Opinion polls have their origin in the 1930ies; their relevance, quality and possible
effects have basically been discussed since then (Schuh 2009: 17 et seq.).
Particularly in the late 1940ies, opinion polls had a negative image in the US. Due to
incorrect forecasts of election results, the media increasingly doubted the polling
agencies (Kaase 1977). In Germany, these doubts were last raised during the
1
This paper has been prepared for the XXIInd IPSA World Congress of Political Science in Madrid,
July 8-12, 2012. This is the first draft; please contact the author before quoting the paper.
1parliamentary elections in 2005. The polling agencies all forecast a clear margin for
the CDU/CSU prior to the elections. In the end, the election results lead to a grand
coalition of CDU/CSU and SPD. Aside from the doubts regarding the forecasts of the
agencies, there are concerns that voters could be influenced by the poll results and
particularly that their voting decision could be manipulated. Basically, experts assume
that the voters’ decisions are no longer only based on personal preferences, but that
voters increasingly consider which behaviour can be expected from the other voters
(Irwin/van Holsteyn 2002: 92).
As was expected, the concerns about possible influencing factors were followed by
first papers that dealt with the effects of the perception of opinion polls or the public
opinion (Gallup/Rae 1940; Simon 1954; Gallup 1965; Lupri 1969; de Bock 1976;
Noelle-Neumann 1980; Donsbach 1984). Looking back on these studies, one can
see that the theoretical expectations are more like ad-hoc assumptions relating to
influence mechanisms, which are substantiated theoretically to different extents. The
Spiral of Silence, the Theory of Normative Conformity as well as the Rational Choice
Theory are used as a theoretical background, for example, mainly for explaining
tactical, strategic voting behaviour (for this, mainly see the works of Mutz 1994,
1998). The different effects assumed for the poll results can be found in individual
hypotheses2:
The most quoted effect of published polls is stated in the bandwagon hypothesis. The
hypothesis states that the election winner forecast by the opinion polls continues to
gain votes, since people prefer being on the winning side. The hypothesis assumes
that people can gain satisfaction alone from changing sides (Mutz 1994). This
switching to the majority opinion, which can lead to a “last-minute swing” (Noelle-
Neumann 1980) just before the elections, is interpreted in different ways. The best
known and frequently quoted explanation for this lies in the theory of the Spiral of
Silence according to Noelle-Neumann (1980), which “[describes] the changes of
public opinion as a process whose dynamics develop from assumptions of individuals
about the opinion of the majority” (Schulz 2011: 223). Regarding the desire to be on
the winning side, Noelle-Neumann assumes that most voters actually do not have
this ambition (1980: 19). She assumes that the fear of being isolated forces voters
onto the side of the party that is supported by the majority. If, due to the poll results
and the public mood, voters have the impression that they are part of the minority
with their intended vote, they will no longer state their opinion in public and will switch
to the majority opinion to prevent being isolated. In contrast, Schmitt-Beck interprets
the bandwagon effect in a more rationalistic way as “low information rationality”
(Schmitt-Beck 1996: 268). Here, undecided, less-involved voters choose the
supposed winner, since, due to their lack of knowledge, they trust the social majority
and therefore do not have to spend any money on gathering information.
The underdog hypothesis is the counterpart of the bandwagon hypothesis. It
assumes that the election loser forecast by the opinion polls can gain additional votes
due to pity. However, this effect cannot only be explained by pity; voting for the
underdog can also be caused by a certain type of cynicism. Schoen (2002) describes
this as defiance towards the supposed election winner.
It shows that there is an explanation both for the sympathy for the assumed stronger
party and for the sympathy for the expected weaker party (Brettschneider 2000).
1
A summary of the hypotheses regarding the effects of opinion polls was presented for the first time
for Germany by Brettschneider (1991).
2According to this, there is a combination of effects, which could neutralize each other
in the aggregate.
There also are two hypotheses concerning the effects on voter turnout: one of them
assumes the effects of a clear election result, the other the effects of a virtually open-
ended result. It is assumed that a close run forecast by the opinion polls should
immediately lead to an increased participation probability, since voters can only then
be safe to assume that their vote could make a difference. This assumption is
formulated in the mobilisation hypothesis. The other hypothesis, the abstention
hypothesis, states that voters do not participate in elections if the result seems
relatively clear, because they feel they cannot influence the result; the benefit seems
to be too small (de Bock 1976).
Two other more specific statements or sub-hypotheses result from this assumption,
which differentiate between supporters of the assumed loser and those of the
assumed winner. The defeatism hypothesis states that the probability that supporters
of the election loser as presented by the opinion polls take part in the election is
lower, since they assume that their vote would not change anything (Brettschneider
2000). On the other hand, the lethargy hypothesis assumes that the supporters of the
winner of the opinion polls do not bother to go and cast their vote. They assume it to
be no longer necessary and are convinced that the effort is wasted (de Bock 1976;
Brettschneider 2000).
These assumptions, which basically relate to avoiding costs, require rational
considerations on the part of the voters. However, rational action can not only relate
to voter participation, but also to the actual voting decision. It is assumed that poll
results or forecasts regarding the outcome of elections cause people to become
concerned about their vote being wasted and have an influence on tactical, strategic
voting. These assumptions are formulated in the ‘wasted vote’ and the tactical vote
hypotheses.
The ‘wasted vote’ hypothesis implies that supporters of smaller parties switch to other
parties as soon as the opinion polls communicate that their party might not be able to
manage the five-percent hurdle required to get into parliament.
Instead, they give their vote to one of the larger parties, choosing the one they
believe to be the lesser evil (Reumann 1983). This is not a change in opinion but a
tactical decision. The ‘wasted vote’ thesis (Schoen 1999) postulates that rational
voters want to avoid their vote being wasted at the election. This would be the case,
however, if the party they actually supported fails to clear the five-percent hurdle,
since their vote would not have any significance (Brettschneider 1992). In addition,
Reumann brings up the question whether poll results have even greater significance
for smaller parties, since every published rating between 3 and 5 percent could be
either an announcement of death or first aid (Reumann 1983).
The tactical vote hypothesis, on the other hand, formulates an assumed effect of poll
results on the splitting of votes, which could help a smaller party manage the five-
percent hurdle contrary to the hypothesis described above (Hopmann 2010). It is
assumed that supporters of larger parties, for example, lend the smaller coalition
partner their vote in order to help realise the desired coalition. Now and again, the
larger parties have called for this kind of strategic voting in their campaigns in the
past few years. The aim of preventing an absolute majority could be another reason
for voters giving their vote to a party other than their preferred one (Brettschneider
1992).
The assumptions regarding cognitive effects present themselves on a more higher-
order level. Here, it is simply assumed that the publication of opinion polls actually
enables the development of specific expectations concerning the outcome of an
3election. Expectations regarding the chances of success of individual parties and
possible coalitions can only be generated on the basis of information about the
current public opinion. Cognitive effects thus describe influences on the expectations
of all eligible voters. This process can be referred to as higher-order, since the
influencing of the development of expectations must precede the hypotheses on the
effects of opinion polls described above.
Due to the data available as well as the fact that the election campaigns prior to the
parliamentary elections in 2009 were quite uneventful, this paper will only analyse the
hypotheses on mobilisation and abstention effects as well as the bandwagon and the
underdog effects. Furthermore, cognitive effects on expectations regarding possible
coalitions will be examined.
3. Methodological problems
There are only few research papers in Germany which deal with the empirical
examination of the hypotheses described above. The first comprehensive analysis of
the effects of published poll results was presented by Frank Brettschneider in 1991.
Brettschneider’s paper surely is an exemplary analysis of the opinion poll data
available at that time. However, one could criticise that it examines the influence of
perceived poll results on the voting decision on the basis of self-assessments
provided by the eligible voters (Maier/Brettschneider 2009: 321 et seq.). Generally,
the question arises as to what extent eligible voters can actually provide valid
information about the factors that influenced their voting decision. In experimental
social psychology, the predominant opinion is that people can only provide
information about the result of a decision process, not about the actual decision
process (for example, see Nisbett/Wilson 1977).
Furthermore, in the past few years, there have been attempts to verify the
hypotheses with the aid of experiments (de Bock 1976; Navazio 1977;
Maier/Brettschneider 2009). Experimental methods have the advantage that they are
generally better-suited for proving causal effects than the analysis of polling data.
Furthermore, they can be tailored exactly to the empirically examined hypotheses. In
this way, it is possible to artificially generate situations such as a party in danger of
failing because of the five-percent hurdle and to examine their effects empirically.
The disadvantage of experimental analysis approaches is their often quite disputable
external validity. The subjects of the online experiment of Maier and Brettschneider
were confronted with slightly manipulated poll results and then directly asked about
their political attitudes and their intended voting behaviour. Such an analysis design
should facilitate proving the effects of opinion results on voting behaviour, since the
stimulus is set directly prior to acquiring the response variables. However, this does
not constitute a particularly realistic setting. Therefore, it is all the more remarkable
that Maier and Brettschneider cannot prove any effects of the perceived poll results in
their analysis. One could speculate that this could be due to their non-representative
student population.
Aside from panel surveys, rolling cross-section (RCS) surveys are particularly well-
suited for analysing effects of poll reporting, which have increasingly found their way
into empirical election research in the last years (Johnston/Brady 2002; Romer et al.
2004). Such RCS surveys are characterised by the fact that the data is acquired over
an extended period of time before the election. The initial sample is divided into
several so-called cross-sections, which are spread over the different survey days in
such a way that the data acquired on every individual day can be interpreted as the
4result of a random sample of the population (for details, see Kenski 2004). In this
way, the dynamics of the electoral campaign can be analysed exactly for every
individual day. Such data also makes it possible to add the poll results published on
the different days as external information. On the basis of such data, it is possible to
analyse empirically whether and how election polls influence expectations regarding
the outcome of an election and voting behaviour.
Two analyses were presented for the German parliamentary elections in 2005, which
used RCS data in order to analyse the effects of election polls empirically
(Faas/Schmitt-Beck 2007; Faas et al. 2008). These analyses pushed research a
large step forwards, but display a special problem. The main problem is that RCS
surveys must be understood as hierarchically structured data sets. The level-1 units
are the respondents, the level-2 units are defined by the day of the survey. If the poll
results published on the different days are added to such data, they must be treated
as level-2 variables. As a consequence, the effects of the poll results on expectations
regarding possible coalitions and voting behaviour cannot be analysed in the context
of simple single-level models. The significance of the effects of the poll results is
estimated on the basis of a much too high number of cases, since the respondents of
a day are not independent from each other with respect to the poll results due to the
identical information context. Therefore, there is a risk of finding significant effects,
which would turn out to be non-significant if the estimation had been made on the
basis of the correct number of cases.
4. Data and analysis strategy
4.1. Data base
The RCS data set analysed here was acquired in the period from 29 July 2009 to
26 September 2009. The basic population is the German-speaking population of the
Federal Republic of Germany living in private households with at least one land line,
who was entitled to vote in the 2009 parliamentary elections (method report
GLES1201 2009: 4). The survey was conducted in the form of a CATI survey and
comprises 6,008 respondents. From the 6,008 cases of the data set, 3,083 (51.3%)
belong to the main sample, 2,180 (36.3%) cases stem from the overdraft (reserve
numbers of the main sample) and 745 (12.4%) stem from a sample taken at a later
point in time. It was necessary to take an additional sample, since the polling agency
miscalculated the number of telephone numbers required to obtain sufficient
interviews (see method report GLES1201 2009). Thus, the planned number of
telephone numbers to be used rises from 80,000 to 94,400. The examination period
for the following analyses only starts on 03 August 2009, since the first days have to
be excluded due to an insufficient number of cases. The number of level-2 units thus
goes down from 60 to 55 days.
The data set of the RCS election campaign study was supplemented with the data of
the published ratings of the weekly voter polls during the survey period. The
supplementation of the survey data is limited to the publications of the following
institutes: forsa, Infratest-dimap and Forschungsgruppe Wahlen. This procedure is
different from the procedure applied for the previous studies by Faas and Schmitt-
Beck (2007) as well as Faas et al. (2008); since the coverage is similar, this is
considered to be the more logical form of operationalisation. This limitation results in
a reduced variation of the poll results over time. However, a subsequent review
showed that this does not make a substantial difference for the analyses described in
5the following. The three institutes published 22 opinion polls on 21 different days
during the observed period. The respectively most current value was used for
generating the data set, which assigns one poll result to every survey day. For the
one day on which two of the polling agencies published results, an average value
was generated.
In order to take into consideration that the interpretation of journalists and presenters
also plays a role in reports about poll results, opinion poll reporting shall be
operationalised as information context in a second step. To this end, there is the
possibility to combine the RCS data with the information from the media data content
analysis of the main television news shows (GLES 1401), which was also conducted
in the context of the GLES. Among other things, assessments of the parties' chances
for the elections were made on the basis of poll results in the period from 28 June
until 26 September 2009. The statements on the parties’ chances were coded into
“small/smaller than”, “medium/same as" and "good/better than". The effect of positive
as well as negative assessments of the parties’ odds shall be analysed in this paper.
The information taken from the media data content analyses was added to the 55
analysis days with a time lag of one day, since a large part of the people interviewed
per day were interviewed prior to the evening news shows. Furthermore, the day-
related information is stretched over two days, since it is assumed that the
statements perceived can still have an effect one day later. Papers from media effect
research show that the recollection of the information presented in news shows only
starts to fade after two to three days (Dams 2003, Krause/Gehrau 2007). For these
analyses, the information was stretched over two days; therefore, the test is rather
conservative. In the multilevel models, the information about the assessments of the
parties’ chances is examined separately for public service television channels and
private channels, since differences in quantity and quality can be expected
depending on the respective group of channels. On public service channels, a more
neutral coverage should become apparent alone by the frequency of judgemental
statements. In a general consideration, it also shows that on private channels, 52
statements were made on good chances and 55 statements on bad chances; on
public service channels, 21 positive and negative judgemental statements each were
made altogether.
4.2. Analysis strategy
Since it is assumed that the data to be analysed contains objects of different levels,
the formulated hypotheses must be tested on the basis of multilevel models. The
hierarchically-structured data set consists of the objects of the individual level (level
1) and those of the context level (level 2). It is presumed that every object of level 1
can be represented as an element of an object of the next higher category (Ditton
1998: 11). In this analysis, the respondents are the objects of the individual level, and
the days are the units of the context level. The survey day thus is the information
context, in which the respondents develop their voting intentions and their
expectations regarding possible coalitions. Due to the shared context, it is assumed
that the respondents of one day are more alike than respondents of different days.
As explained, the information context is operationalised in this analysis through the
respectively most recent poll results and, as an alternative, through the coverage on
the basis of the poll results. Since the dependent variables of this analysis are
dummy variables, multilevel binary logistic models were estimated. In the 1, the
variables contain the information whether the person is planning to cast a vote,
6whether the person is planning to vote for a certain party or whether the person
interviewed expects that one of the examined coalitions will form the government.
Stata 11 was the analysis software used; the parameter estimation was executed
with the full maximum likelihood estimation algorithm.
It is pointed out here that this analysis strategy also has several weaknesses. For
instance, the cases of the second level of the data set are generally regarded as a
random sample from a theoretically defined basic population in the multilevel
analysis. However, this is not the case for the data presented here. Strictly speaking,
the data of our level-2 variables is time series analysis data. With time series
analyses, there often is the problem of auto-correlated error terms, i.e., that the value
of a day is correlated with the value of the day before. Therefore, the values are not
independent of each other but are similar to each other. Accordingly, the standard
errors tend to be underestimated (see Hox 2002: 98 et seq.). Altogether, the
methodological problems of this analysis strategy are far less serious than those of
single-level models.
5. Results
First, the developments of the intention to cast a vote, the intention to vote for the
individual parties and the expectations regarding possible coalitions are described
over the period of the RCS survey. There can only have been effects of events during
the election campaigns if these developments show a certain variance during the
crucial election phase. The significance of this variance and the intensity of the poll or
media effects are then examined in the multilevel analyses.
5.1. Descriptive findings
On the one hand, the graphs show the percentage proportions of the dependent
variables for the individual days; on the other hand, they display smoothed data,
which represents the weekly average. Furthermore, the respectively relevant poll
results are represented in the form of stacked bars.
Figure 1 shows the trend for the people’s intention to vote. The proportion of
respondents who state that they will definitely vote is displayed. Considering the
development over the 55 days, it shows that this figure lies at around 73 percent at
the beginning of the crucial election campaign phase, but goes up to nearly 98
percent one day before the election. During the period in-between, the proportion is
mostly between 78 and 90 percent; a slight, continuous increase can be seen on the
basis of the weekly average. This is in accordance with the expectation that the
willingness to vote increases the nearer the election day comes. Such a development
could also be attributed to the fact that – due to the election polls – the respondents
perceive the election result to be more and more uncertain the closer the election day
comes. The stacked bars represent the percentage point distances between the
totalised poll results of the respective coalition possibilities. The development of the
bars shows that the decreasing distance between the coalition of Christian
Democrats (CDU/CSU)/Liberals (FDP) and the coalition of Social Democrats
(SPD)/Greens just before the election develops virtually parallel to the increasing
intention to vote. This indicates a possible mobilisation effect.
7Figure 1: Development of the intention to vote as well as the closeness of the poll results over a period
from 03 August to 26 September 2009
Considering the developments of the five well-established parties in the German
parliament, it becomes clear that there is a typical level of support for every party
altogether, around which there are significant daily variations (not shown in the
graph). Particularly for the Greens and the Left Party, this level of support changes by
tendency over time.
Figure 2: Development of the intention to vote as well as the poll results for the Greens in the period from
03 August until 26 September 2009
8Figure 3: Development of the intention to vote as well as the poll results for the Left Party in the period
from 03 August until 26 September 2009
The published poll results for the parties are placed behind the development of the
intention to vote again in the form of a bar diagram. However, only few findings can
be read from the graphs regarding the effects of poll results on the voting decision by
means of pure “eye balling”. Considering the intention to vote for the Greens in
Figure 2, there is a divergent development of the intention to vote and the poll results
towards the end of the examination period. While the poll ratings for the Greens
slightly go down, there is an increasing intention to vote for the party. This could
indicate an effect according to the underdog hypotheses.
Considering the development of the expectations regarding possible coalitions in
Figures 4 and 5, there is a clear advantage for the coalition between CDU/CSU and
FDP in the early phase of the 55 days. The respondents do not seem to believe that
there will be another grand coalition at this point in time. The closer the election day
comes, the closer the two coalition models are regarding the perceived likelihood.
About 10 days prior to the election, the expectations regarding a grand coalition are
even higher than the expectations of a coalition between CDU/CSU and FDP. One
day prior to the election, the coalition between CDU/CSU and FDP lies ahead of the
grand coalition again.
9Figure 4: Development of the expectations regarding a grand coalition as well as the poll results of SPD
and CDU/CSU in the period from 03 August until 26 September 2009
Figure 5: Development of the expectations regarding a coalition between CDU/CSU and FDP as well as
the poll results of CDU/CSU and FDP in the period from 03 August until 26 September 2009
Therefore, the question arises as to whether the changes in the expectations
regarding possible coalitions can be attributed to the poll results. Considering the
development of the totalised poll results within the survey period, which can be read
from the displayed bars, there is only little variance for the poll results of the two
coalition partners altogether. However, if the proportion values for the individual
parties are used as a reference, it shows that the perceived likelihood of a coalition
between CDU/CSU and FDP tends to go down when the poll results for the
10CDU/CSU sink, and the perceived probability of a grand coalition increases when the
poll ratings for the SPD increase. When considered more closely, however, the
direction of causality is not clear. Particularly Figure 4 shows that the proportion of
the people interviewed who expect a grand coalition increases first; the poll results of
the SPD go up at a later point in time.
5.2. Intraclass correlation
A special feature of multilevel models is that the unexplained variance of the
dependent variable is divided into two parts: into an individual level variance (σ2e)
and into a context level variance (σ2u0). In logistic multilevel analyses, the variance
proportion on level 1 (σ2e) is π2/3 (Snijders/Bosker 1999: 224). On the basis of the
two variance proportions as well as the total variance, the intraclass correlation
coefficient (ICC) can be calculated. For this purpose, models are estimated which do
not yet contain any explaining variables, so-called intercept-only models (Hox 2002:
14 et seq.). Therefore, the ICC corresponds to that proportion of variance which can
be attributed to the fact that the units of the individual level belong to the different
context units (Engel 1998: 83 et seq.). Furthermore, the ICC can also be understood
as a measure of likeness of the individuals on one survey day (see Hox 2002: 15).
The greater the ICC, the more alike the respondents of one survey day are with
respect to their political attitudes, and the more different the respondents of different
days are. An ICC other than zero thus indicates that there potentially are effects of
level-2 variables on the dependent level-1 variable. In the relevant literature, an ICC
other than zero is therefore often regarded as the prerequisite for an estimation of a
multilevel model to make sense (see for many others Luke 2004: 17-23).
Table 1: Intraclass correlation coefficients of the model-specific dependent variables
Dependent variables ICC N
Intention to vote 0.021*** 5800
Vote intended for: CDU/CSU 0.000 4855
Vote intended for: SPD 0.002 4855
Vote intended for: FDP 0.000 4855
Vote intended for: Green Party 0.006 4855
Vote intended for: Left Party 0.000 4855
Expected coalition: Grand coalition 0.030*** 5831
Expected coalition: Coalition CDU/CSU and FDP 0.028*** 5831
Significance levels: * p≤0.05; ** p≤0.01; *** p≤0.001.
Table 1 shows that for the intention to vote and the two expected coalitions, only a
small proportion of variance can be attributed to the fact that some of the units
belong to the units of the second level. The models for explaining the votes intended
for specific parties nearly all have an ICC of zero. There only is an ICC slightly above
zero, which is non-significant, however, for the SPD and the Greens; therefore, the
votes intended for these parties need not be examined separately. The votes
11intended for the individual parties thus do not vary significantly over the days of the
survey period; therefore, the prerequisite regarded to be necessary for calculating
multilevel models is not provided here.3
For the model examining the intention to vote, it shows that 2.1 percent of the
variance can be attributed to the survey days. The corresponding proportion for the
expectations regarding the possible coalition is 3.0 or 2.8 percent. Therefore, for
these three dependent variables, the persons interviewed on one day are slightly
more alike than the persons interviewed on different days.
The other results are displayed in the following for the dependent variables with a
significant variance over the relevant days. First, the models dealing with the
intention to vote are presented, and then the results for the expected election
outcome. On the context level the opinion polls are examined, initially. If there is
context level variance left, the models are complemented by the information from the
media coverage.
5.3. Opinion polls as information context
5.3.1. Intention to vote
Table 2 shows the results of the multilevel analysis regarding the influence of a close
outcome of the election on the intention to vote, on the basis of which the
mobilisation and abstention hypotheses can be examined. To be more exact, the
closeness of the shares of the votes between the possible coalitions of CDU/CSU
and FDP versus SPD and the Greens as well as a coalition between CDU/CSU and
FDP versus a grand coalition. In a first step, a model was estimated which only
contains individual characteristics. The demographic parameters gender, age and
education are checked. Furthermore, political interest, party identification and the
perception of opinion polls also go into the analysis. It is assumed that political
interest has a mobilizing influence on voter participation (Caballero 2005).
Furthermore, voters who are committed to a party are more likely to vote. The
perception of opinion polls was taken into consideration for the model, since it can be
expected that this variable moderates the influence of the published opinion polls on
the intention to vote. From model 2 on, the variables of the context level are added
step by step. First, a trend variable is introduced, which models the approaching of
the election day in order to check for natural campaign mobilisation. Another level-2
variable is added, which displays the closeness of the poll results between the
coalitions of CDU/CSU and FDP versus SPD and the Greens. In order to be able to
account for the closeness of the poll results of the coalitions, the poll ratings for the
respective parties were summed up first; then the difference between the two
coalitions was calculated (see Kirchgässner 1990). Model 3 initially represents the
overall model for the influence of the closeness of the poll results between a coalition
of CDU/CSU and FDP versus a coalition of SPD and the Greens with an interaction
term added to the model between the closeness of the opinion polls and the
perception of opinion polls. The interaction term is introduced in order to be able to
examine the influence of the poll results under the condition that these were actually
3
Despite the lacking variance on level 2, the multilevel models were estimated for the individual
parties for checking purposes. No effects of poll results could be proven in terms of the bandwagon
hypothesis or underdog hypothesis. The main influencing factors for explaining the intention to vote
are the known factors from the Michigan Model: party identification, issue
orientations, candidate orientations (Schoen/Weins 2005).
12perceived. In models 4 and 5, the variable which presents the closeness between the
grand coalition and the coalition between CDU/CSU and FDP is first introduced in
identical form, followed by the interaction term for the closeness of the poll results
and the perception of opinion polls.
On level 1 of all five models of table 2, it shows that, aside from the demographic
parameters, political interest, party identification and the perception of opinion polls
have a statistically significant effect on the intention to vote. The separate effect
"perception of opinion polls" first and foremost seems to reflect intensive attention
towards election campaign reporting. When considering the level-2 coefficients, it
becomes clear that no significant effect of the poll results on the intention to vote can
be proved. Obviously, they have no mobilising or demobilising effects. However, an
empirical proof for a natural election campaign mobilisation as mentioned above
results from this. With every day of the election campaign, the chance of voter
participation increases by 1.1 percent (models 2 and 3) or by 1.5 percent (models 4
and 5).
13Table 2: Binomial logistic multilevel analyses on the effects of poll results on the individual intention to vote
Model 1 Model 2 Model 3 Model 4 Model 5
Odds S. E. Odds S. E. Odds S. E. Odds S. E. Odds S. E.
Level 1
Gender (ref.: female) 0.816* 0.071 0.818* 0.071 0.818* 0.071 0.819* 0.071 0.819* 0.071
Age 1.024*** 0.003 1.024*** 0.003 1.024*** 0.003 1.024*** 0.003 1.024*** 0.003
Educationa (ref.: lower education)
middle education 1.404** 0.159 1.398** 0.158 1.398** 0.158 1.395** 0.158 1.395** 0.158
higher education 1.989*** 0.239 1.995*** 0.240 1.995*** 0.240 1.992*** 0.239 1.992*** 0.239
Political interest 2.823*** 0.143 2.822*** 0.142 2.822*** 0.142 2.822*** 0.142 2.821*** 0.142
Party identification 1.523*** 0.133 1.531*** 0.134 1.531*** 0.134 1.530*** 0.136 1.528*** 0.133
Perception opinion polls 1.258* 0.121 1.227* 0.119 1.254 0.968 1.228* 0.119 0.949 0.490
Level 2
Trend: day 1.011** 0.004 1.011** 0.004 1.015*** 0.005 1.015*** 0.005
Closeness CDU/CSU and FDP vs.
1.036 0.035 1.037 0.035 0.928 0.041 0.928 0.041
SPD/Greens
Closeness CDU/CSU and FDP vs.
SPD/Greens 0.999 0.050 1.028 0.057
*perception opinion polls
Closeness CDU/CSU and FDP vs.
grand coalition
Closeness CDU/CSU and FDP vs.
grand coalition
*perception opinion polls
σ2e 3.29 3.29 3.29 3.29 3.29
σ2u0 0.11*** 0.08*** 0.08*** 0.08*** 0.08**
N (level 2) 55 55 55 55 55
N (level 1) 5280 5280 5280 5280 5280
Significance levels: * p≤0.05; ** p≤0.01; *** p≤0.001.
The displayed standard errors refer to the logit coefficients.
a
lower education = degree from a Hauptschule or less; middle education = degree from a Realschule; higher education = Abitur.
145.3.2. Cognitive effects on expectations regarding possible coalitions
Since no effects of the poll results on the intention to vote could be proven, the
influences of the convictions of the voters regarding the outcome of the election will
be examined in the following.
Acceptable ICC values showed for the expected coalitions so that the corresponding
binomial logistic multilevel models will be displayed in the following. The same as in
the previous analyses, model 1 in table 3 shows the influence of the individual
characteristics first. Aside from the known demographic characteristics as well as the
perception of opinion polls, checks are made for the preference for the respective
coalition in order to eliminate the effect of wishful thinking with respect to the
expectations. In model 2, the poll results of the coalition partners are then introduced
separately, since possible influences could annul each other otherwise. Model 3
contains the interaction terms of the poll results with the perception of opinion polls.
Table 3 shows the effects for the forecast that CDU/CSU and SPD will form the
government as a grand coalition. As becomes clear in model 2, a statistically
significant effect of the published poll results can be proved for this forecast. When
the poll ratings for the CDU/CSU go up by one percent point, the chance that a grand
coalition is expected decreases by 11.2 percent. In contrast, the chance of expecting
a grand coalition increases by 9.8 percent with every additional percentage point for
the SPD. At the same time, the influence of the poll results is supported by the
decreasing variance proportion on level 2. In addition, in model 3, the influence of the
poll results of the SPD is confirmed by a statistically significant interaction effect.
Thus, the perception of opinion polls supports the influence by the poll ratings of the
SPD.
15Table 3: Binomial logistic multilevel analyses on the effects of poll results on the expectation
of a grand coalition
Model 1 Model 2 Model 3
Odds S. E. Odds S. E. Odds S. E.
Level 1
Gender (ref.: female) 0.909 0.056 0.913 0.056 0.912 0.056
Age 0.992*** 0.002 0.992*** 0.002 0.992*** 0.002
Educationa (ref.: lower education)
middle education 1.136 0.101 1.143 0.102 1.135 0.101
higher education 1.111 0.096 1.116 0.096 1.111 0.096
Coalition preference 1.180*** 0.012 1.179*** 0.012 1.181*** 0.012
Perception opinion polls 1.097 0.069 1.083 0.068 0.292 0.057
Level 2
Poll results CDU/CSU 0.899* 0.045 0.927 0.057
Poll results SPD 1.098* 0.042 1.019 0.047
Poll results CDU/CSU*perception
0.938 0.065
opinion polls
Poll results SPD*perception opinion
1.168** 0.062
polls
σ2e 3.29 3.29 3.29
σ2u0 0.09*** 0.05*** 0.05***
N (level 2) 55 55 55
N (level 1) 5482 5482 5482
Significance levels: * p≤0.05; ** p≤0.01; *** p≤0.001.
The displayed standard errors refer to the logit coefficients.
a
lower education = degree from a Hauptschule or less; middle education = degree from a Realschule;
higher education = Abitur.
Table 4 shows the influence on the expectation that the coming government will
consist of CDU/CSU and FDP. Significant effects of the poll results show here, too.
Model 2 shows that the chance of the expectation of a government consisting of
CDU/CSU and FDP increases by 23.3 percent with every additional percentage point
for the CDU/CSU in the opinion polls. For the FDP, the corresponding increase is
14.4 percent. If the interaction terms of the poll results with the perception of opinion
polls are taken into consideration, only the effect of the poll results for the CDU/CSU
is statistically significant on level 2.
16Table 4: Binomial logistic multilevel analyses on the effects of poll results on the expectation
of a coalition between CDU/CSU and FDP
Model 1 Model 2 Model 3
Odds S. E. Odds S. E. Odds S. E.
Level 1
Gender (ref.: female) 1.478*** 0.087 1.470*** 0.087 1.468*** 0.087
Age 1.016*** 0.002 1.016*** 0.002 1.017*** 0.002
Educationa (ref.: lower education)
middle education 1.185* 0.101 1.183* 0.101 1.187* 0.101
higher education 1.795*** 0.149 1.789*** 0.148 1.794*** 0.148
Coalition preference 1.180*** 0.010 1.180*** 0.010 1.180*** 0.010
Perception opinion polls 1.357*** 0.084 1.366*** 0.084 0.001** 0.002
Level 2
Poll results CDU/CSU 1.233*** 0.060 1.138* 0.064
Poll results FDP 1.144* 0.073 1.079 0.073
Poll results CDU/CSU*perception
1.174** 0.073
opinion polls
Poll results FDP*perception opinion
1.14 0.962
polls
σ2e 3.29 3.29 3.29
σ2u0 0.12*** 0.07*** 0.07***
N (level 2) 55 55 55
N (level 1) 5472 5472 5472
Significance levels: * p≤0.05; ** p≤0.01; *** p≤0.001.
The displayed standard errors refer to the logit coefficients.
a
lower education = degree from a Hauptschule or less; middle education = degree from a Realschule;
higher education = Abitur.
For the analysis of the effects of opinion polls, it can be concluded that the
hypotheses regarding the influence on the intention to vote and the voting decision
could not be confirmed. Only the cognitive effects on the expectations regarding the
outcome of the election can be proven. One possible explanation for the different
results of the interaction effects in the analyses of the two expected coalitions is
based on an indirect effect of the poll results: the influencing of the voters by means
of opinion polls does not necessarily have to require that the polls are perceived
directly, since the results are also reflected in the political mood communicated by the
media. This alone makes the influencing of voters possible; in addition, it is also
possible that voters state that they did not perceive actual poll results, simply
because they cannot remember. To some extent, this is examined in the next
section: an analysis of the effects of media coverage.
175.4. Media coverage as information context
The multilevel models which contain the effects of media coverage in the form of
statements on the parties’ chances for the elections are supplemented on level 1 with
the consumption of news programmes on public service and private TV channels.
The variables contain the information as to whether someone saw the news on the
respective channels on none of the past seven days or whether the person watched
them on one to two days (rare viewers) or on three to seven days (frequent viewers).
Altogether, it must be said that statements broadcast on public service channels do
not show a significant effect in any of the models so that the description of the results
concentrates on the effects of statements made in news programmes on private
channels. Furthermore, there are no negative statements on public service channels
regarding the CDU/CSU; that is why the fields in the tables are empty at these
positions. The same applies to the FDP. On the private channels, there was only one
positive statement on one day regarding the SPD; therefore, this is also excluded
from the analyses, since there is no sufficient data.
For the sake of completeness, it is mentioned here that this form of operationalisation
of the information context has no effects on the intention to vote; therefore, the
effects of opinion poll reporting can only be examined for the expectations regarding
possible coalitions.
In table 5, the models for the expectations of a grand coalition are displayed. The
table shows a clear effect of the negative assessments on private channels of the
CDU/CSU’s chances for the election. The likelihood of the expectation of a grand
coalition increases by 83.1 percent when small or smaller chances of the CDU/CSU
of winning the elections were communicated. Due to the negative assessments, the
voters seem to quickly consider the option of a coalition between CDU/CSU and
SPD; this might also be the result of the relatively positive experience made with the
last governing coalition. Furthermore, this immediately suggests that this also
corresponds to the further interpretation of the newsreader. On the other hand, good
or better assessments on private channels of the SPD’s chances of winning make the
likelihood of the expectation of a grand coalition go down by 42.2 percent. Due to the
interpretation of the results, the possibility of a coalition between SPD and Greens is
promoted, which reduces the expectation of a grand coalition. The interaction effects,
which represent the effects of the statements under the condition that the news is
perceived on private channels, are non-significant. Another operationalisation of the
news consumption variable, for example, as a metric variable with consumption on
zero to seven days, does not lead to a deviating result. Generally, it is striking that
consumption of the news does not have a significant influence on the expectation of
a grand coalition.
18Table 5: Binomial logistic multilevel analyses on the effects of media coverage on the
expectation of a grand coalition
Odds S.E.
Level 1
Gender (reference group: female) 0.908 0.055
Age 0.994** 0.002
Educationa (reference group: lower education)
middle education 1.189* 0.106
higher education 1.188* 0.104
Coalition preference 1.178*** 0.012
Consumption news public service (ref.: not watched)
Watched on 1-2 days 0.935 0.090
Watched on 3-7 days 0.916 0.070
Consumption news private (ref.: not watched)
Watched on 1-2 days 1.180 0.102
Watched on 3-7 days 0.984 0.080
Level 2
Assessment of chances for elections CDU/CSU, public
service (ref.: no status)
Negative -- --
Positive 1.584 0.402
Assessment of chances for elections CDU/CSU, private
(ref.: no status)
Negative 1.831* 0.466
Positive 1.107 0.145
Assessment of chances for elections SPD, public service
(ref.: no status)
Negative 0.957 0.124
Positive 0.615 0.230
Assessment of chances for elections SPD, private
(ref.: no status)
Negative 0.703** 0.081
Positive -- --
σ2e 3.29
σ2u0 0.06***
N (level 2) 55
N (level 1) 5538
Significance levels: * p≤0.05; ** p≤0.01; *** p≤0.001.
The displayed standard errors refer to the logit coefficients.
a
lower education = degree from a Hauptschule or less; middle education = degree from a
Realschule; higher education = Abitur
19In the model for the expectation of a coalition between CDU/CSU and FDP, there is
only one significant effect on level 2. Only good or better assessments of the
CDU/CSU’s chances for the elections broadcast on private TV channels increase the
likelihood of the expectation of this coalition possibility (32.0 percent). In these
models, too, a postulated increasing strength of the CDU/CSU results in people
believing in the victory of the coalition between CDU/CSU and FDP. It is noticeable in
this model that consumption of news programmes on the different TV channels is
significant. When the news are watched on public service channels, the chances of
the expectation of a coalition between CDU/CSU and FDP increase significantly. It
does not make a difference whether the news are watched frequently or rarely. In
contrast, the chances of the expectation of a coalition between CDU/CSU and FDP
sinks if the news is watched on private channels. However, the interaction effects
with the consumption of news programmes are not significant either.
20Table 6: Binomial logistic multilevel analyses on the effects of media coverage on the
expectation of a coalition between CDU/CSU and FDP
Odds S.E.
Level 1
Gender (ref.: female) 1.537*** 0.090
Age 1.014*** 0.002
Educationa (ref.: lower education)
middle education 1.183* 0.101
higher education 1.728*** 0.144
Coalition preference 1.181*** 0.010
Consumption news public service (ref.: not watched)
Watched on 1-2 days 1.598*** 0.150
Watched on 3-7 days 1.532*** 0.114
Consumption news private (ref.: not watched)
Watched on 1-2 days 0.792** 0.067
Watched on 3-7 days 0.857* 0.068
Level 2
Assessment of chances for elections CDU/CSU, public
service (ref.: no status)
Negative --
Positive 0.787 0.167
Assessment of chances for elections CDU/CSU, private
(ref.: no status)
Negative 0.692 0.181
Positive 1.320* 0.186
Assessment of chances for elections FDP, public service
(ref.: no status)
Negative --
Positive 1.540 0.405
Assessment of chances for elections FDP, private
(ref.: no status)
Negative 0.860 0.233
Positive 0.729 0.149
σ2e 3.29
σ2u0 0.08***
N (level 2) 5525
N (level 1) 55
Significance levels: * p≤0.05; ** p≤0.01; *** p≤0.001.
The displayed standard errors refer to the logit coefficients.
a
lower education = degree from a Hauptschule or less; middle education = degree from a
Realschule; higher education = Abitur
Altogether, the results from the models with published poll results are confirmed on
level 2; however, there were no additional findings.
216. Conclusion
This paper was intended to examine the effects of published opinion polls as well as
additional media coverage on voters prior to the parliamentary elections in Germany
in 2009. The examinations were conducted on the basis of multilevel analyses;
therefore the poll results as well as the statements regarding the individual parties’
chances for the elections made in news programmes also go into the analyses as
context characteristics.
It already showed when the ICCs were calculated for the individual analysis models
that the intention to vote does not vary systematically on the individual level
depending on the survey day. This leads to the interpretation that the electoral
campaign in general and opinion poll reporting in particular virtually failed to leave
their mark on people in 2009. The lack of effects of the published election polls as
well as the media coverage was also confirmed for the intention to vote. In contrast to
this, there are cognitive effects for the expectations regarding possible coalitions. The
published poll results as well as statements in news programmes construct an image
of the political mood, by which the voters are guided when developing their beliefs.
With respect to the results of the multilevel analyses on the basis of the RCS data,
the statements only apply to the aggregate level, since individual random samples
are provided for every day, and therefore different persons were interviewed every
day. Thus, it is possible that influences on the decision-making process of individuals
are equalled out in the aggregate in the end. Panel data is necessary for examining
the intra-individual influencing of the decision-making process; this is the only way to
show whether the individual voters change their voting intention or other political
attitudes within the period of the election campaign and whether this could possibly
be attributed to perceived opinion polls. However, this does not lessen the relevance
of the provided results, since the outcome of every election is the aggregation of all
individual decisions in the end.
With respect to the assumptions formulated at the beginning regarding an increased
controllability of the voters by means of short-term factors during the election
campaign, there was less systematic volatility than expected. Replication studies on
the example of other elections must show whether this can be attributed to the
election campaigns in 2009, which were generally perceived to be uneventful and
free of conflict, or whether the effects of election campaigns are ascribed too much
power.
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