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Polarization Between the Rich and the Poor? The
Dynamics and Structure of Redistributive
Preferences in a Comparative Perspective
Xavier Romero-Vidal
1
and
Steven M. Van Hauwaert
2,3
1
Department of Politics and International Studies, University of Cambridge;
2
University of
Surrey, Guildford, United Kingdom;
3
Political Science Department, Institute for Management
Research, Radboud University Nijmegen, The Netherlands
Abstract
Citizens’ support for redistribution varies largely between and within countries. An
important empirical challenge in this field is the scarcity of comparative data, which
this study overcomes by designing a novel time-series cross-sectional dataset that
spans more than three decades in seven European countries. Using nearly 300 sur-
veys and a dyadic ratios algorithm, we estimate aggregate redistributive preferences
for each country, as well as for population strata within countries based on household
income. We then ask to what extent support for redistribution varies across the rich
and the poor. We find that citizens are not systematically becoming more reluctant
toward or more supportive of redistribution. While redistributive preferences of the
rich and the poor do not strictly move in parallel, there is no polarization between
the two. Moreover, both the demand for redistribution and the preference gap be-
tween the rich and the poor evolve in a cyclical way.
Key words: time-series cross-sectional analysis; survey data; polarization; redistributive preferences;
comparative politics; parallelism.
In his foundational work Politics: Who gets what, when, [and] how,Lasswell (1936)
addresses a series of issues that remain recurring questions in politics today. The notion
of politics as the resolution of how resources will be distributed has sparked much polit-
ical economy and public policy research related to inequality and redistribution. At the
same time, this extensive scholarship has overlooked an important and equally necessary
question, namely “who wants what and when.” Classic political economy models have
Corresponding author: Xavier Romero-Vidal, The Department of Politics and International Studies, The
Alison Richard Building, 7West Road, Cambridge, CB39D, United Kingdom. Email: xr221@cam.ac.uk.
International Journal of Public Opinion Research
V
CThe Author(s) 2021. Published by Oxford University Press on behalf of The World
Association for Public Opinion Research.
This is an Open Access article distributed under the terms of the Creative Commons Attribution
License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse,
distribution, and reproduction in any medium, provided the original work is properly cited.
doi:10.1093/ijpor/edab015
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underestimated the role citizens play in the inequality–redistribution puzzle, in spite of
the extensive macro polity literature highlighting its importance (Erikson et al., 2002).
As a direct consequence, the question of what people want in this domain needs further
clarification.
Systematic insights into redistributive preferences are often hampered by the scar-
city of available measures. Our study sets out to fill that gap by providing unique meas-
ures of redistributive preferences and make them available to the public. By means of a
comprehensive time-series cross-sectional design, we model the extent to which these
preferences evolve across European democracies. Furthermore, we explore variation
within individual countries, i.e., whether the preferences of different segments of the
population move in different ways. In particular, we analyze the way income influences
the structure and evolution of redistributive preferences. By distinguishing between the
preferences of the rich and the poor within each country, we assess whether they di-
verge or converge over time and which income stratum primarily drives the observed
dynamics.
Drawing from a large number of survey data sources and using a dyadic ratios al-
gorithm, we construct country-year measures of redistributive preferences for coun-
try populations and three different income quintiles (low, middle, and high) in seven
European democracies: France (1995–2017), Germany (1984–2016), Great Britain
(1981–2017), Netherlands (1978–2017), Norway (1989–2017), Sweden (1985–2017),
and Switzerland (1993–2017). The underlying dataset is comprised of 880 country-
year observations and relies on 299 surveys, 1,384 item series, and 8,244 administra-
tions. Our findings provide key insights into the comparative macro polity. Although
there is some shared variance, we find little evidence of a cross-national trend in re-
distributive preferences. Within each country, public opinion trends do not have a
systematic trajectory, but are rather cyclical. In line with extant scholarship, we find
that different income groups, and most notably the rich and the poor, demand differ-
ent levels of redistribution. Yet, our results also indicate there is more independent
movement (less parallelism) between the rich and the poor in Europe compared to
what scholars find in the USA. The preference gap between the rich and the poor is
rather stable over time, meaning there is no clear polarization or depolarization be-
tween the two.
As a whole, our in-depth comparative analysis of the dynamics and structure of re-
distributive preferences broadens our understanding of the macro polity, public opin-
ion, and issue publics, most notably beyond the typical Anglo-Saxon scope in this field.
Additionally, the preference measures and overarching dataset provide an important re-
source for scholars with an interest in mass representation and comparative political be-
havior, both at the individual and aggregate level. It can serve as a valuable tool for the
discipline to gain additional insights into the relationship between inequality and redis-
tribution, as well as the empirical study of democracy more generally.
Introducing redistributive preferences
Since the 1930s, public opinion scholarship has included an important conceptual de-
bate about the nature of public opinion itself: What constitutes public opinion (and
what does not)? Contrary to most “essentially contested concepts” in political science
(Gallie, 1955), there appears to be quite some agreement in the overall conceptualization
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of public opinion (see Converse, 1987). In line with much of the literature, we therefore
think of public opinion as the collective or aggregate of true or long-term individual pol-
icy preferences, attitudes, and beliefs regarding a harmonized or specific set of issues
and questions (Key, 1961;Page & Shapiro, 1992;Stimson, 1991).
1
Such a macro-societal conception of public opinion has a number of important
implications. Not only does it provide an aggregate reflection of the so-called “breeding
ground” of political phenomena, but it also allows political actors to respond to societal
evolutions and develop appropriate political strategies (e.g., Druckman & Jacobs, 2006;
Stevenson, 2001). In turn, the matching of political supply with political demand can be
seen as a core characteristic of representative democracy (Dahl, 1971;Key, 1961;
Manin, 1995). With that in mind, an accurate and comprehensive understanding of
public opinion also has relevant normative implications (Erikson et al., 2002;Stimson et
al., 1995;Stimson & Wager, 2020).
While there have been important debates about the nature and movement of public
opinion as a whole, recent academic work also examines public opinion in more disag-
gregated forms, tracking the preferences of different population strata within each coun-
try. Most notably, public opinion scholarship explores preferences related to inequality,
wealth, and income distribution, and particularly how these may differ between (in-
come) groups (Enns & Kellstedt, 2008;Enns & Wlezien, 2011;Gilens, 2005,2009;
Kelly & Enns, 2010;Page & Jacobs, 2009;Ura & Ellis, 2008). Most such studies agree
that different societal groups—whether defined by income, education, sophistication,
race, or gender—have distinct demands.
While social and cultural issues such as immigration increasingly dominate the
agendas across advanced democracies, the economy—as a political issue—continues to
play a prominent role in party competition (Williams et al., 2016), electoral outcomes
(Singer, 2011), and policy priorities (Bevan & Jennings, 2014). This is unsurprising con-
sidering how governments have faced recurrently periods of economic and financial
hardship throughout the last decades, most notably the energy crisis in the late 1970s,
the global economic recession in the early 1980s, the economic downturn in the early
1990s, the financial crisis in the late 2000s, the European debt crisis in the 2010s, and
the on-going health crisis related to COVID-19. In light of the ensuing inequalities and
polarization, citizens—and the political arena more generally—remain attentive to eco-
nomic questions and concerns regarding government interventions (Bellucci et al.,
2012;Jennings & Wlezien, 2011).
The role of government remains largely a directional or spatial issue for which
“reasonable people can take either side” (Stimson, 1991). Citizens position themselves
alongside a continuum of dis/agreement with respect to government involvement and
redistribution by demanding more or less of it. This is in line with earlier theorizations,
for example, by Page and Shapiro (1992), who argue that increasingly available survey
data allow us to capture aggregated public demands or sentiments that concern relative-
ly specific and highly salient societal points of contention over time. With that in mind,
we understand peoples’ opinions for redistribution, which we refer to as redistributive
preferences, as a comprehensive construct that describes the evolution of a set of
1
Authors largely agree that we can measure public opinion through some form of aggregation of individual
survey items (Berinsky, 1999;Miller & Stokes, 1963;Page & Shapiro, 1992;Stimson, 1991), although the pre-
cise specifications of how to appropriately do this remains up for debate. We return later to how we propose to
do this.
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collective preferences or aggregated opinions regarding the levels and impact of redistri-
bution in society.
Such domain-specific interpretations of public opinion, as opposed to more univer-
sal ones like the “policy mood” (Bartle et al., 2019,2020;Erikson et al., 2002;McGann
et al., 2019), are not uncommon. We refer, for example, to studies utilizing government
spending preferences (Jacoby, 2000;Shapiro & Young, 1989;Wlezien, 2004), mass pref-
erences in policy-specific domains (Soroka & Lim, 2003;Wlezien, 1995), or policy-
specific moods (Coggins & Stimson, 2019;Romero-Vidal, 2020;Van Hauwaert &
English, 2019;Cinalli & Van Hauwaert 2021). Extant research studying preferences
regarding redistribution often remains on the individual level and singles out partial
components of redistributive preferences, ranging from targeted indicators, such as the
support for the introduction of a two-tier welfare system (Bay et al., 2013) to more gen-
eral measures, such as attitudes toward welfare policies (Svallfors, 2012), support for re-
distribution (Gonthier, 2017), attitudes toward redistributive policies (Breznau &
Hommerich, 2019;Ferna´ndez & Jaime-Castillo, 2018;Finseraas, 2009;Peters & Ensink,
2015) or, more holistically, economic conservatism (Caughey et al., 2019). Alternatively,
some studies rely on a group of survey items to estimate latent measures of preferences
regarding redistribution. Cavaille´ and Trump (2015), for example, distinguish between
support for redistribution from the rich and support for redistribution to the poor, while
Roosma et al. (2013)identify seven different dimensions of redistribution.
Our operationalization of support for redistribution is more comprehensive. In this
regard, we build on Lupu and Pontusson (2011), who study “aggregate support for re-
distributive policies.” Yet, while they measure preferences using a single survey item,
we estimate latent preferences relying on a large number of survey questions. This
allows us to account for the potentially multifaceted nature of our latent measure.
Additionally, Lupu and Pontusson limit their analysis to the percentage of middle-
income citizens who think that government is responsible for reducing income differen-
ces, whereas we also want to take the preferences of the first and fifth quintiles (rich and
poor, respectively) into consideration.
Due to a lack of consistent data, even in countries with long-standing survey tradi-
tions, previous studies often remain limited in their temporal and geographic scopes.
This leaves unexplored the nature and movement of the “median voter” and the citizen-
ry as a whole. We add to this scholarship by designing comprehensive country-year
measures of redistributive preferences for seven European democracies using a dyadic
ratios algorithm. In what follows, we examine their structure and the patterns of vari-
ance between and within countries, comparing the aggregate opinions of different in-
come groups. This will allow us to substantively assess whether redistributive
preferences of the rich and poor become more or less polarized in the time period under
analysis.
Data specifications: estimating redistributive preference measures
We rely on a unique dataset of redistributive opinion measures from seven countries:
France (1995–2017), Germany (1984–2016), Great Britain (1981–2017), the
Netherlands (1978–2017), Norway (1989–2017), Sweden (1985–2017), and Switzerland
(1993–2017). With the exception of some longer series in the Netherlands and shorter
series in Switzerland and France, they tend to go from the 1980sto2017. The dataset
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includes an extensive selection of thematically grouped items, which have been asked on
at least two separate occasions, from a wide range of high-quality national and inter-
national opinion surveys. We include all questions concerning positions toward the wel-
fare state, social benefits, and public spending in fields that directly enhance
redistributive policies (and therefore excluding defense, culture, and environmental
protection spending). We also include items dealing directly with redistribution, tax-
ation, and the role of the state in reducing inequalities, as well as items related to the
desired degree of government involvement throughout economic and business function-
ing.
2
Table 1includes an overview of the total number of questions (often across differ-
ent surveys) and administrations in every country.
For each survey item, we compute the percentage of citizens wanting more redistri-
bution and divide it by the cumulative percentage of those wanting more and those
wanting less redistribution, while using each survey’s weight to account for design and
sample biases. Higher values of the resulting “survey marginals” indicate relative pref-
erences for more redistribution, while lower scores indicate preferences for less redistri-
bution. It is important to note that absolute levels of redistributive preferences are less
relevant here, since we seek to record and examine changes over time, which renders
these values in and of themselves change variables. Marginals from questions repeated
over time form independent item series.
The diverse frequencies of item series within a country complicate the identifica-
tion of comparable trends. Some survey items we include have been asked twice, some
more frequently. Yet, consistent item series that allow for comparisons through time
and across space remain scarce given variations in question wordings, response catego-
ries, ordering of the survey, sampling methods, or the absence of data points following
survey-specific or rotating modules. Yet, some examples of longer series in our coun-
tries inquire about the size of the public sector (Sweden, 31 administrations), the bal-
ance between tax reductions and social benefits (Great Britain, 31 administrations), the
desirability of income difference (Switzerland, 24 administrations; Netherlands, 21
administrations), and general state intervention (France, 15 administrations).
Even if some individual series provide reasonable coverage, conclusions drawn
from a single series are likely to be subject to several types of bias and measurement
error (Diamantopoulos et al., 2012). Different item series might have different biases
depending on the issues that it includes, the precise wording, and the response options
it provided (Zaller & Feldman, 1992). While relying on a single item can provide im-
portant insights, it is paramount to note that it also restricts the analysis of public opin-
ion in its classical sense, namely as a latent construct with a long-term equilibrium
(Key, 1961;Page & Shapiro, 1992;Stimson, 1991).
Our starting point is, therefore, a set of item series for each country. In order to
group them and get a single measurement of the latent support for redistribution in
each of the seven countries, we employ a dyadic ratios algorithm (Stimson, 1991,2018).
This method is conventional in macro polity research (Bartle et al., 2011,2019;Enns &
Kellstedt, 2008;Kelly & Enns, 2010;Stimson et al., 1995), but much more limited
across issue-specific applications of public opinion largely due to data restrictions.
Notable exceptions use the algorithm to construct measures of presidential approval
(Carlin et al., 2015a,2015b,2018), immigration opinions (Jennings, 2009;Van
2
For a detailed country-by-country list of surveys, question wordings, years of measurement, and degree of
repetition of the included items, we refer to Section A in the Supplementary Materials.
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Hauwaert & English, 2019), Muslim-related issues (Cinalli & Van Hauwaert 2021, sup-
port for independence (Romero-Vidal, 2020), environmental concerns (Brulle et al.,
2012), and gender equality (Koch & Thomsen, 2017), among others.
The dyadic ratios algorithm presupposes that each single-item time series can
be considered a valid indicator of redistributive preferences, and therefore the
change between any two values within that time series (a dyad ratio) is a relative in-
dicator of change in redistributive preferences over time. Through an iterative pro-
cess, the algorithm estimates the covariance between the dyadic ratios of each item.
From this covariance, it then calculates validity measures for the different dyad ratio
series and uses these to estimate the best possible latent measure. The dyad ratio ser-
ies combined and adjusted according to their covariance compose redistributive
preference values at each available user-defined interval (in our case, every year). In
order to maintain accurate patterns of variance over time, we use these data-driven
estimates without applying any further smoothing. In other words, we combine the
independent single-item series and estimate a combined redistributive preference
measure for each country.
3
We highlighted earlier that different survey items tap into different components of
the latent redistributive preference measure and, therefore, gauge it to various extents.
In turn, that means—almost like in a factor analysis—each item series has a separate
loading on the underlying measure, depending on how closely it relates to the latent
construct. On average, the first dimension of the estimation captures nearly 60 percent
of the overall variance (see Table 2).
4
This supports our idea that redistributive
Table 1
Data sources.
Start
date
End
date
Time
points
Item series
(questions)
Survey items
(administrations)
N%N%
France 1995 2017 23 65 18.79 311 15.09
Germany 1984 2016 33 50 14.45 214 10.38
Great Britain 1981 2017 37 55 15.90 482 23.39
Netherlands 1978 2017 40 48 13.87 417 20.23
Norway 1989 2017 29 39 11.27 147 7.13
Sweden 1985 2017 33 55 15.90 264 12.81
Switzerland 1993 2017 25 34 9.83 226 10.97
Total 220 346 2,061
Note. A visual overview of the individual series per country are available in Section B of the
Supplementary Materials.
3
Alternative estimation tools produce similar results and are available from the authors under request.
These cross-validations include (a) an estimation with an IRT algorithm (McGann, 2014) instead of the dyadic
ratios algorithm (Stimson, 2018), (b) tracking long item series as proxies for the estimated measures, and (c)
excluding these longest item series and compared the estimated measures with and without them.
4
We refer to Section C in the Supplementary Materials for more detailed country-by-country descriptive
statistics and item series factor loadings.
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preferences are to a large extent captured as a one-dimensional construct.
5
We standard-
ize the measures using country means because the absolute values are dependent on
each country’s individual series and we are mostly interested in change over time.
Figure 1displays the corresponding measures of redistributive preferences in each
country over time.
While scholars tend to argue there is a neo-liberal trend across advanced democra-
cies (e.g., Schram, 2015), this is not something we see translated in the evolution of
European publics, at least not to the same unambiguous extent. Rather, the defining
feature of redistributive preferences is cross-country variability, without a clear-cut
cross-national pattern. Redistributive preferences appear to have a cyclical character
in all countries, alternating periods of higher and lower demand for redistribution.
The standard deviations of the redistributive preference measures in Table 2further
illustrate the cyclical nature of these preference measures. Most notably, redistribu-
tive preferences remain relatively stable in France and Switzerland, while they move
much more in the Netherlands and Germany.
Redistributive preferences covary—although not perfectly—over time and a trend
in one country appears to be reflected in other countries. The average inter-item covari-
ance of 0.10 between the seven measures indicates that, while most of their movement
remains country-specific, they share some cross-country movement.
6
We include the
results from a principal factor analysis in the final two columns of Table 2. It further
illustrates there is a shared consideration across most countries that accounts for more
than a third of the cross-country variance (EV ¼2.51).
7
This suggests a certain degree
of parallelism in redistributive preferences between countries.
A descriptive examination of redistributive preferences indicates some common
movement across European democracies, which could be referred to as a “European re-
distribution mood.” Yet, there is important country-specific movement of redistributive
Table 2
Descriptive statistics across years, per country.
Years Mean Std. Dev. Explained variance Factor Uniqueness
France 23 65.498 2.654 66.64 0.824 0.261
Germany 33 70.087 4.049 53.03 0.724 0.398
Great Britain 37 67.884 3.993 52.17 0.620 0.362
Netherlands 40 66.643 6.560 42.90 0.416 0.656
Norway 29 69.740 3.538 69.81 0.492 0.581
Sweden 33 68.393 3.391 66.77 0.707 0.303
Switzerland 25 67.640 3.161 47.95 0.068 0.831
Average 31 67.889 4.582 57.04
5
Although the DRA allows for the estimation of a second dimension, estimating a second dimension with
the data problems typical of survey marginals is hazardous and largely untested. Furthermore, when we do es-
timate that second dimension, it makes little to no substantive sense.
6
We refer to Section D in the Supplementary Materials for full tables of alpha test scales.
7
A factor analysis presents only a summarized analysis in this case, as it does not fully appreciate the dynam-
ic time-dependent nature of the data. We recognize this and use the analysis only to highlight there is a hint of
some shared dynamic across countries. We refer to Section E in the Supplementary Materials for more
detailed information related to the factor analysis.
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preferences as well.
8
Based on the uniqueness estimates in Table 2, about half of the
variance remains country-specific on average. This does not only indicate national par-
ticularities—and, thus, independent movement, but it also suggests that the movement
and variance of citizens’ redistributive preferences vary within countries.
Redistributive preferences across income groups
Within-country patterns of variance
Considering the extensive country-specific variance, it is difficult to speak of a clear and
homogeneous cross-national trend. The question remains, however, whether the public
preference structure can be explained by patterns of variance within national publics. In
and of itself, this would not be surprising, as objective group interests, such as income,
are likely to shape the redistributive preference structure (Enns & Wlezien, 2011). There
is extensive evidence that lower-income groups typically favor more redistribution and
welfare spending, while more affluent citizens prefer more market freedom (Erikson &
Tedin, 2019;Kuhn, 2013;Luttig, 2013;Peters & Ensink, 2015). However, little is known
about how the observed variance between income groups evolves through time.
Regarding the evolution of group opinion, the existing literature offers two con-
trasting views. A first perspective holds that group opinions, whether defined by income
Figure 1
Standardized redistributive preference measures, by country.
Note. All measures have been standardized using country-means. Higher values indicate
more support for redistribution, while lower values indicate less support for redistribu-
tion. Vertical lines indicate election years.
−4
−2
0
2
−4
−2
0
2
−4
−2
0
2
1975
1980
1985
1990
1995
2000
2005
2010
2015
1975
1980
1985
1990
1995
2000
2005
2010
2015
1975
1980
1985
1990
1995
2000
2005
2010
2015
France Germany Great Britain
Netherlands Norway Sweden
Switzerland
Standardised redistributive preferences
8
This is already clear from the negative loadings returned for Germany, Sweden, and Switzerland. It sug-
gests a negative linear association between the “European redistribution mood” and the country observations.
In other words, redistributive preferences in these countries do not follow the supposed overall pattern.
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(Kelly & Enns, 2010), gender (Kellstedt et al., 2010), education (Enns & Kellstedt,
2008), or party identification (Ura & Ellis, 2012), track each other closely enough
through time to speak of a uniform or parallel movement. While this is particularly
prominent in the USA, to the best of our knowledge comparative evidence of parallel-
ism remains scarce. An alternative perspective argues that, in addition to being different,
group opinions also change differently through time, i.e., they do not move in parallel
and are rather asymmetric. From a comparative perspective, Peters and Ensink (2015)
find such different evolutions in support for redistribution between income groups (see
also Brooks & Manza, 2006).
9
If group opinions are truly evolving asymmetrically, the
question remains whether they are diverging or converging over time. A conclusive an-
swer eludes us at the moment, as the scarcity of cross-sectional time-series dampens the
study of the potential polarization of redistributive preferences between the rich and the
poor.
In order to estimate and examine the evolution of income group opinions, we divide
country populations into income quintiles and focus on the top, middle, and bottom
groups. For simplicity reasons, we refer to the former and latter groups as the rich and
the poor, respectively. Since survey data usually offer income ranges instead of absolute
values, the number of citizens in each group does not always represent an exact quintile.
Usually, the group with lower income represents a higher share of the sample than the
top quintile. We correct these errors by using the weight measure for each survey. For
each income group, we repeat the estimation process detailed in the previous section: we
calculate the marginals of our selected items and then estimate the central tendency of re-
distributive mass preferences for that income group through a dyadic ratios algorithm.
The result is a single redistributive measure for each income group in every country.
Figure 2displays these preference series for the low-, middle-, and high-income
categories in each country. Since the absolute values are dependent on each country’s
individual series, we standardize the measures using cross-income group country
means. It is immediately evident there is a persistent preference gap between income
groups. Higher-income groups generally demand less redistribution than their lower-
income counterparts, which is in line with previous findings (Peters & Ensink, 2015).
Table 3further validates that lower-income groups—on average—desire more re-
distribution (mean ¼70.1) than middle-income groups (mean ¼69.1) and their more
affluent counterparts (mean ¼62.4). This observation holds for most countries, with
the notable exception of Scandinavian countries, where the middle groups demand
more redistribution than lower-income groups. A set of paired t-tests in the last two col-
umns of Table 3further suggests that—in nearly all instances—the levels of support for
redistribution between income groups differ significantly (at least, on average and
through time). The t-tests also suggest that the level of redistributive support by the
middle-income groups is closer to the level of the low-income groups than that of the
high-income groups, with average cross-national differences of 3.6% and 19%, respect-
ively. This is a similar observation to what Peters and Ensink (2015)found for a more
limited time frame (2002–2010)in25 European countries.
Researchers have shown that the redistributive preferences of the American middle
class typically approach those of the rich, diverging from what some scholars tend to
refer to as a pronounced “underclass” (Enns & Wlezien, 2011;Soroka & Wlezien,
9
Even those supporting the parallel publics hypothesis find asymmetric movement between some income
groups (notably the poor vs. others) and in certain time period (Enns & Wlezien, 2011).
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2008). This illustrates the welfare gap in the USA, as well as the growing levels of in-
equality between the poor and other socio-economic classes. At the same time, our find-
ings illustrate that patterns from the USA are not necessarily generalizable to other
contexts. After all, we do not observe the same kind of evolution across Europe.
Without exception, we find that middle-income groups across Europe tend to situate
their redistributive preferences closer to those of the poor than those of the rich. Often
times, it is not even close.
Table 3further indicates that low-income groups hold relatively stable redis-
tributive preferences, whereas demands for redistribution are more volatile among
higher-income groups. This pattern, which holds across most countries, might appear
counter-intuitive at first sight, seeing how Converse (1964)and Zaller (1992)imply
greater stability in opinions for the more “sophisticated” strata. Yet, because of the
common overlap between income and education, we can argue that the top quintile
pays most attention to political and economic changes. In turn, this is why wealthier
citizens are able to update their preferences more frequently, in reaction to both polit-
ical and economic events (Enns & Kellstedt, 2008;Erikson et al., 2002;Ura & Ellis,
2008). Moreover, demand for redistribution among the rich might be conditioned to
external factors such as a crisis or an election, whereas lower-income groups might
demand more redistribution by default.
The movement of group opinions is not fully independent, as we observe in Figure 2
and Table 3. When support for redistribution increases for one income group, it tends to
increase for the other income groups within a country as well. The average within-country
inter-item correlation of 0.40 indicates that, while redistributive preferences covary, they
Figure 2
Redistributive preferences, per income group and by country.
Note. All measures have been standardized using cross-income group country-means.
Higher values indicate more support for redistribution, while lower values indicate less
support for redistribution. A more detailed visualization of each series, including their
fitted slopes and the corresponding slope coefficients, can be found in section E of the
supplementary materials.
−4
−2
0
2
−4
−2
0
2
−4
−2
0
2
1975
1980
1985
1990
1995
2000
2005
2010
2015
1975
1980
1985
1990
1995
2000
2005
2010
2015
1975
1980
1985
1990
1995
2000
2005
2010
2015
France Germany Great Britain
Netherlands Norway Sweden
Switzerland
Preferences of low−income groups
Preferences of middle−income groups
Preferences of high−income groups
Standardised redistributive preferences
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Table 3
Descriptive statistics across years, per income group and by country.
Low-income groups Middle-income groups High-income groups DIncome groups (t-tests)
Years Mean Std. Dev. Mean Std. Dev. Mean Std. Dev. Low vs. middle Middle vs. high
France 23 66.515 3.259 66.199 2.974 62.047 3.624 0.740 (0.428)8.111*(0.512)
Germany 33 73.625 5.341 71.226 4.048 65.776 5.349 2.735*(0.877)5.989*(0.910)
Great Britain 37 68.369 4.096 65.349 5.173 60.621 5.831 6.751*(0.447)11.859*(0.399)
Netherlands 40 69.808 6.760 67.174 6.032 60.704 8.260 2.967*(0.887)7.156*(0.904)
Norway 29 72.087 4.136 74 .673 3.884 63.140 5.444 5.145*(0.503)10.959*(1.052)
Sweden 33 69.912 3.691 70.428 3.993 60.980 5.280 2.352*(0.219)17.697*(0.534)
Switzerland 25 70.115 4.151 69.234 3.337 64.969 3.752 0.754 (1.168)3.795*(1.124)
Average 70.145 5.145 69.084 5.351 62.438 6.047 3.571*(0.297)19.033*(0.349)
Note. Descriptive statistics are from unstandardized estimations. *p.05;t-tests include standard errors in parentheses.
11POLARIZATION BETWEEN THE RICH AND THE POOR?
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do not move in perfect symmetry.
10
This independent movement is nicely captured by the
factor analysis of redistributive preferences across income groups presented in Table 4.
Within each country, all series load on a single factor that accounts for an average of 58%
of the variance across income groups. The uniqueness estimates indicate redistributive
preferences exhibit a certain degree of parallel movement, but to a much lesser extent than
earlier research typically shows.
11
Our analyses so far indicate common movement across Europe, shared move-
ment between income groups and income group-specific movement. The question
we, then, ask is whether certain income groups show more common movement than
others. In that regard, Table 5presents the results of a cross-national principal fac-
tor analysis of the preference measures for each income group. We notice that high-
income groups share more variance than the other income groups, thereby indicat-
ing more common movement across countries. We also see this reflected in the more
sizeable uniqueness measures for low- and middle-income groups. One might specu-
late that low-and middle-income groups are more influenced by national dynamics,
whereas high-income groups are more permeable to international trends (and each
other).
While the ensemble of analyses so far only presents indicative evidence, we do no-
tice that the variance of our preference measures depends on the objective group
interest (income), the individual country setting, and the temporal evolution. A more
detailed analysis of variance (ANOVA) suggests that, on average, the preference meas-
ures are indeed characterized by differences between income groups (27.7%), across
countries (10.2%), and through time (14.5%).
12
Figure 3plots the explained variance by income and time in each country.
Following Enns and Wlezien’s (2011)suggestion that the variance explained by time
provides a measure of parallel movements across income groups in the same unit, we
find more parallel movement in France, Great Britain, and the Netherlands than in
other countries. This is in line with earlier observations from Figure 2and Table 3.
Conversely, income groups in the Scandinavian countries explain the preference struc-
ture to a much greater extent than in other countries.
Polarization of redistributive preferences?
In addition to structural differences in levels, Figure 2highlights that periods of conver-
gence and divergence between income group opinions alternate. The combination of
heterogeneous movement between income groups and the cyclical nature of the prefer-
ence dynamics result in a fluctuating and contingent preference gap. To examine this
gap and its potential persistence or even enlargement in more detail, we calculate the
through-time difference in standardized redistributive preferences of the rich and the
poor. Figure 4plots the evolution of this distance, as well as the corresponding fitted
line, providing original insights into the potential polarization dynamics between in-
come groups.
10
We refer to Section G of the Supplementary Materials for detailed correlations and alpha scales.
11
If we examine the underlying trend across income groups and countries, we find that a first factor explains
about 40% of the variance in redistributive preferences and, thus, accounts for more than a third of the com-
mon movement.
12
For more detailed information about the ANOVA of the preference measures, we refer to Section I in the
Supplementary Materials.
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The fitted lines indicate the extent to which the gap between the redistributive
preferences of the rich and the poor follows a consistent trend. A negative slope would
suggest that group preferences converge, whereas a positive slope would indicate
increasing levels of polarization. Yet, as the overall slope coefficient approaches zero in
all countries, it is safe to say we find little to no cross-national evidence of systematic
Table 4
Factor analysis of the preference series within each country.
Factor Uniqueness Eigenvalue
France Low-income groups 0.792 0.338 2.036
Middle-income groups 0.926 0.142
High-income groups 0.742 0.411
Germany Low-income groups 0.514 0.721 0.939
Middle-income groups 0.681 0.537
High-income groups 0.461 0.769
Great Britain Low-income groups 0.870 0.243 2.527
Middle-income groups 0.955 0.088
High-income groups 0.926 0.142
Netherlands Low-income groups 0.748 0.440 1.890
Middle-income groups 0.798 0.363
High-income groups 0.833 0.306
Norway Low-income groups 0.828 0.314 1.498
Middle-income groups 0.833 0.306
High-income groups 0.344 0.882
Sweden Low-income groups 0.970 0.060 2.581
Middle-income groups 0.961 0.077
High-income groups 0.847 0.282
Switzerland Low-income groups 0.578 0.733 0.716
Middle-income groups 0.387 0.850
High-income groups 0.547 0.701
Table 5
Factor analysis of the preference series across countries.
Low-income groups Middle-income groups High-income groups
Factor Uniqueness Factor Uniqueness Factor Uniqueness
France 0.740 0.355 0.626 0.420 0.487 0.476
Germany 0.458 0.628 0.475 0.507 0.663 0.316
Great Britain 0.333 0.615 0.608 0.376 0.627 0.334
Netherlands 0.022 0.703 0.493 0.670 0.598 0.545
Norway 0.559 0.598 0.565 0.337 0.505 0.427
Sweden 0.765 0.291 0.678 0.304 0.748 0.219
Switzerland 0.636 0.514 0.405 0.578 0.600 0.448
EV 2.169 2.173 2.602
Note. We include more details of the factor analysis in Section G of the Supplementary Materials.
13POLARIZATION BETWEEN THE RICH AND THE POOR?
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polarization in redistributive preferences between the rich and the poor. The distance
between their preferences is not constant or symmetric, but shows discontinuous peri-
ods of polarization with a long-term equilibrium. For example, in Germany we find a
distinct period of polarization between the mid-1990s and early 2000s. This is then fol-
lowed, as in every other instance, by a period of preference convergence.
Such heterogeneity further highlights that differences between income groups are
irregular across countries. We have already alluded to this on various occasions by posit-
ing that not all movement is shared (see also Table 3). Yet, the preference gap itself
does not reveal which population stratum is actually driving the observed short-term
polarization periods. To tackle this, we analyze which income group moves further
away from the previous equilibrium when the preference gap grows. In particular, we
are interested in the relationship between both low- and high-income group preferences
with those of the middle category.
Table 6presents the results of different OLS regressions, with all variables
standardized. The first three models report pooled estimates of the middle-income
group preferences predicted by its own lag and different combinations of the low-
and high-income group preferences. It is important to note these models are not
meant to imply or assess causal relationships among the redistributive preference
series. They are merely a tool to identify potential asymmetry in the movement.
Models four to six estimate the first difference of middle-income group preferences
expressed as a combined function of its own lag and the first differences of the
lower- and higher-income group series. This ensures that inferences derived from
Figure 3
Relationship of between-group and through-time variance, by country.
Note. The figure shows the R2values for two ANOVAs of redistributive preferences
with income group and time as independent variables, respectively.
France
Germany
Great Britain
Netherlands
Norway
Sweden
Switzerland
.2
.3
.4
.5
.6
Income (R−sq)
.2 .3 .4 .5 .6
Time (R−sq)
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the models are not the result of spurious relationships among non-differenced in-
come group preference series.
The different models consistently illustrate that the redistributive preferences of
middle-income groups are more strongly related to the preferences of low-income
groups than high-income groups. Comparing the first two models, we notice the coef-
ficient of low-income groups is about 20% larger than the coefficient of higher-
income groups. This remains in the combined third model, but the difference between
them is not statistically significant (p>.05).Thefourthmodeldrawsasimilarsub-
stantive conclusion: Conform to earlier indications, the association between low- and
middle-income group preferences is considerably stronger than the association be-
tween middle- and high-income group preferences. Here, the difference between
them is statistically significant (p.05). With the same interpretation from the differ-
enced model, we can be sure that our cross-national findings are not sheer artifacts of
temporal dynamics in the raw data.
It is clear from Figure 4that the difference in redistributive preferences of high-
and low-income groups is most dynamic in Germany (sd ¼1.165). In other words, the
movement of the preference gap indicates that polarization in Germany fluctuates quite
a bit through time. With that in mind, we address two additional questions. First, we
wonder whether the initial findings also hold if we examine Germany independently.
Model 5indicates this is effectively the case. Even more, as the coefficient for high-
income groups is not significant in Germany, we find clear evidence that redistributive
preferences of middle-income groups move together with the preferences of low-
income groups. Second, we also examine if Germany might have been driving the ear-
lier pooled results from models 1–4. Model 6endorses and strengthens the earlier
Figure 4
Distance between high- and low-income groups, by country.
Note. Measures are calculated from redistributive preferences that have been standar-
dised using country-means (see Figure 2). Higher values indicate more polarisation,
while lower values indicate less polarisation.
−2
0
2
4
6
−2
0
2
4
6
−2
0
2
4
6
1975
1980
1985
1990
1995
2000
2005
2010
2015
1975
1980
1985
1990
1995
2000
2005
2010
2015
1975
1980
1985
1990
1995
2000
2005
2010
2015
France Germany Great Britain
Netherlands Norway Sweden
Switzerland
Polarisation measure
Fitted values
Polarisation of redistribitive preferences
15POLARIZATION BETWEEN THE RICH AND THE POOR?
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findings, suggesting there is no significant association between changes in preferences
among the high- and middle-income group preferences when we exclude Germany
from the sample. Overall, this provides additional credence to our substantive
takeaways.
Altogether, we find clear evidence of asymmetry in the underlying dynamics of re-
distributive preferences. That is, the cyclical patterns of more or less polarization are
not the result of symmetric changes between the redistributive preferences of low- and
high-income groups. Rather, our findings suggest that middle-income group preferen-
ces are more strongly associated with low-income group preferences, while high-income
group preferences exhibit more idiosyncratic movement. As a result, the movement of
income group preferences may be thought of as an asymmetrical process with separate
explanatory variables. Even though we do not find any evidence of long-term
Table 6
Middle-income series as a function of lower- and higher-income group series.
Middle-income group
preferences
t
DMiddle-income group
preferences
t
(1)(2)(3)(4)(5)(6)
pooled pooled pooled pooled Germany remaining
Middle-income
group
preferences
t1
0.399*0.391*0.289*0.380*0.558*0.346*
(0.058)(0.060)(0.060)(0.055)(0.175)(0.058)
Low-income group
preferences
t
0.480*0.382*
(0.056)(0.062)
High-income group
preferences
t
0.392*0.215*
(0.060)(0.062)
DLow-income
group
preferences
t
0.307*0.293*0.319*
(0.054)(0.126)(0.062)
DHigh-income
group
preferences
t
0.108*0.171 0.082
(0.055)(0.150)(0.061)
Constant 0.019 0.013*0.013*0.015*0.020 0.021*
(0.049)(0.052)(0.048)(0.053)(0.163)(0.055)
Observations 213 213 213 213 32 181
Number of
countries
7777 1 6
R-squared 0.487 0.424 0.516 0.337 0.441 0.317
Sigma_u 0.040 0.030 0.029 0.032 0.036
Sigma_e 0.722 0.765 0.703 0.771 0.745
Rho 0.003 0.002 0.002 0.002 0.002
Chi-square 0.298
Note. All entries are OLS regression coefficients (standard errors in parentheses); Cross-national models in-
clude country-specific fixed effects; *p0.05 (two-tailed tests); Results from alternative specifications for
models 3and 4can be found in Section J of the Supplementary Materials. All substantive implications re-
main the same.
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polarization in redistributive preferences, our analysis reveal the short-term asymmetric
movement between income groups.
Conclusion
The interdependence between the socio-economic environment and political outputs
such as public policies is part of the empirical and normative framework of contempor-
ary democracies. According to Easton (1965), citizens and their preferences (public
opinion) provide the necessary link between the two. Applied to the inequality–redistri-
bution puzzle, this places citizens’ redistributive preferences at the center of the ana-
lysis. Yet, the role of citizens and their preferences for redistribution in this equation
remains underdeveloped. We believe that the primary reason is a lack of data and corre-
sponding measures enabling time-series cross-sectional analyses. This study aims to pro-
vide a solution to this problem. Drawing from an unprecedented number of public
opinion surveys, we design a set of redistributive preference measures that cover an aver-
age of about three decades across seven European democracies. Through a dyadic ratios
algorithm, we estimate measures for the population as a whole, as well as population strata
based on income. The resulting measures enable new insights into when certain segments
of the population update their demands for more or less redistribution. Moreover, its
time-series cross-sectional character allows us to assess the extent to which we can speak
of trends within, between, and beyond countries. Our measures offer a relevant and pub-
licly available resource for scholars interested in the evolution of redistributive preferences
and, more generally, the dynamics of public opinion across Europe.
Our analysis takes a three-folded approach. First, we explore the dynamics of na-
tional redistributive preference measures. On average, we find no evidence that
European citizens are systematically becoming either more reluctant toward or more
supportive of redistribution. Put differently, there is no single cross-national and longi-
tudinal trend toward more (or less) demand for redistribution. While we observe some
common movement among European publics, much of the observed movement remains
unique to the country. This leaves considerable variance to be explained by within-
country dynamics. Nonetheless, our analysis suggests that around half of the variation
of redistributive preferences is shared across countries.
Second, we delve into the disparities in both levels and movement of redistributive
preferences of low-, middle-, and high-income groups. Regarding preference levels, the
data reveal a persistent gap between income group opinions. We find that, as expected,
low-income citizens consistently demand more redistribution than their middle- and
high-income counterparts. The distance between the groups is not constant but fluctuates
through time in a non-systematic but cyclical way. The preferences of the middle group
are closer to those of the low-income group across Europe. Regarding the movement of
group preferences over time, we observe more variation in the preferences of high-income
groups. At the same time, while income groups within and across countries share some
movement, we find that considerable movement remains unique to each income group.
In a third and final step, we explore the fluctuating and contingent preference gap
between low- and high-income groups. The evolution of this gap over time shows no
evidence of any systematic trend toward polarization between the rich and the poor. At
the same time, while examining the short-term cyclical nature of the preference struc-
ture, we show that patterns of convergence and divergence are not the result of
17POLARIZATION BETWEEN THE RICH AND THE POOR?
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symmetric change between the redistributive preferences of the rich and the poor.
Whereas American scholarship typically shows that the redistributive preferences of the
middle class resemble those of the rich, our analysis identifies a strong association be-
tween low- and middle-income preferences, both in levels and changes. Consequently,
high-income citizens support redistribution considerably less, although their preferen-
ces are more volatile. Given the idiosyncratic movement of their preferences, our evi-
dence suggests that the rich drive and maintain the preferences gap.
Our study presents an unprecedented analysis of redistributive preferences across
European democracies, as well as how they differ between income groups. It starts to fill
an important gap in various literatures, ranging from aggregate public opinion and com-
parative political behavior in Europe to empirical democracy and comparative political
economy studies more generally. Yet, perhaps even more importantly, our study illus-
trates that research and findings from the USA should not be automatically exported to
other (European) democracies. Particularly when it comes to public opinion, there is
something to be said about “American exceptionalism.” The extensive parallelism of pref-
erences that notable scholars in the field find in the USA, or Anglo-Saxon countries more
generally, is not something we see translated to mainland Europe. While we provide a first
analysis and observation, the question of why this is the case remains. We speculate this
might be related to the differences in electoral systems, but it might also relate to Anglo-
Saxon countries being liberal-market economies where large segments of the middle class
simply “go private,” eroding the social contract and therefore aligning much more closely
with the rich.
The novel dataset we present in this study allows for the comprehensive analysis of
redistributive preferences as a dependent, independent, or control variable. Our dataset
can facilitate further analysis of various components of a broader comparative macro
polity and may be used to study a wide variety of research questions: What shapes redis-
tributive preferences? Which group interests are accounted for in politics and redis-
tributive policy more specifically? What does income group heterogeneity mean for the
inequality–redistribution puzzle? Our data allow researchers to provide new insights
into these questions and to obtain a broader and deeper understanding of the dynamics
of public preferences and their interplay with the political and economic context.
Supplementary Data
Supplementary Data are available at https://doi.org/10.7910/DVN/1XRAYZ
and IJPOR online. Replication data are available at https://doi.org/10.7910/
DVN/TBPW4Z.
Acknowledgements
We would like to thank four anonymous reviewer and the journal editors for
their extensive comments, as well as their patience with our requests for add-
itional time. We appreciate both and take neither for granted. We would like to
express our gratitude to John Bartle, Ryan Carlin, Sebastian Dellepiane-
Avellaneda, Juan J. Ferna´ndez, Tim Hellweg, Greg Love and Christian Welzel
for valuable input on various versions of this manuscript (and its spin-offs).
18 INTERNATIONAL JOURNAL OF PUBLIC OPINION RESEARCH
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This paper was part of a research project we presented in the “Macro Opinion
in Comparative Perspective” workshop at the 2018 ECPR Joint Sessions. We
thank John Bartle and Tim Hellwig for bringing such a great group of scholars
together, as well as all participants for their valuable feedback, comments and
suggestions.
Conflicts of interest: None declared.
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Biographical Notes
Xavier Romero-Vidal PhD is a postdoctoral Research Associate at the University of
Cambridge. He holds a PhD in political science from the Leuphana University of
Lu¨ neburg. His main research area is the study of the evolution of public opinion and
political behaviour from a comparative perspective.
Steven M. Van Hauwaert PhD is an Associate Professor (Senior Lecturer) in
Comparative Politics at the University of Surrey and the principal investigator of the
Global Public Opinions Project (GPOP). His primary research interests are in the fields
of comparative political behavior and public opinion, as well as populism and other chal-
lenges to democracy. His most recent academic contributions have appeared in, among
others, the European Journal of Political Research, the European Political Science Review,
Politics, and West European Politics. He is also an associate editor of the ECPR journal
Political Research Exchange (PRX) and the Methods and Measurement section of
Frontiers in Political Science.
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