Z Vgl Polit Wiss (2013) (Suppl) 7:137–157
DOI 10.1007/s12286-013-0168-3
Aufsätze
Corruption and citizens’ satisfaction
with democracy in Europe: what is the
empirical linkage?
Daniel Stockemer · Aksel Sundström
Abstract: This article evaluates the influence of corruption on how individuals assess the state
of democracy in their country. Distinguishing between individual perceptions of small-scale corruption and macro-level corruption trends, we are interested in the question: which of the two
indicators influences citizens’ judgments of their regime? Controlling for ten micro-level factors
(i.e. individuals’ satisfaction with the government, economy, education system, their participation in social activities, their feeling of public safety, and their assessment on whether they are
discriminated against, as well as the four demographics gender, age, education and income) and
four contextual factors (i.e. development, economic growth, democratic stock, and income inequalities) our hierarchical linear model offers some nuanced results. First, we find that an individual’s assessment of whether the police and the judges are corrupted influences his or her
satisfaction with democracy. Second, our results indicate that the same finding does not apply for
the broad macro-level corruption indicator; macro-level corruption is rather unrelated to how a
person judges the quality of democracy in his or her country.
Keywords: Corruption · Individuals’ satisfaction with democracy · Macro-level corruption trends
Korruption und Bürgereinstellungen zu Demokratie in Europa:
Was ist der empirische Zusammenhang?
Zusammenfassung: Der Artikel untersucht den Einfluss von Korruption auf die Einstellung von
Individuen hinsichtlich ihrer Bewertung des Demokratiegrades ihrer Länder. Hierbei unterscheiden wir zwischen der individuellen Wahrnehmung von Korruption auf der Mikroebene sowie
Korruptionsphänomenen auf der Makroebene und fragen danach, welcher dieser beiden Indikatoren die Regimebewertung durch die Bürger beeinflusst. Unsere Mehrebenenanalyse überprüft
zehn Faktoren der Mikroebene (individuelle Zufriedenheit mit der Regierung, Wirtschaft, dem
Published online: 19.10.2013
© Springer Fachmedien Wiesbaden 2013
Prof. D. Stockemer ()
School of Political Studies, University of Ottawa,
120 University Social Sciences Building, Ottawa, ON K1N 6N5, Canada
e-mail: [email protected]
A. Sundström
Department of Political Science, University of Gothenburg,
Box 711, 405 30 Gothenburg, Sweden
e-mail: [email protected]
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D. Stockemer and A. Sundström
Bildungssystem, ihrer Beteiligung an sozialen Aktivitäten, das Empfinden öffentlicher Sicherheit, und ihre Einschätzung, ob sie bezüglich der vier demographischen Merkmale Geschlecht,
Alter, Bildung und Einkommen diskriminiert werden) und vier Kontextfaktoren (Entwicklung,
Wirtschaftswachstum, Demokratisierungsgrad und Einkommensungleichheit). Die Analyse bietet
dabei ein differenziertes Ergebnis: Erstens stellen wir fest, dass die individuelle Einschätzung, ob
Richter oder die Polizei korrupt sind, die Zufriedenheit mit der Demokratie beeinflusst. Zweitens
legt unsere Analyse nahe, dass ein ähnliches Ergebnis bezüglich Korruption auf der Makroebene
nicht gibt. Korruption auf der Makroebene steht in keinem Zusammenhang mit der individuellen
Bewertung der demokratischen Qualität eines Landes durch dessen Bürger.
Schlüsselwörter: Korruption · Individuelle Zufriedenheit mit Demokratie ·
Korruptionsphänomene der Makroebene
1 Introduction
In his famous 1863 Gettysburg Civil War Address, American President Abraham Lincoln
defined a democracy “as a government of the people, by the people and for the people.”
Implicit in Lincoln’s famous definition is the concept of responsive democracy. A responsive democracy is characterized by three features: (1) it allows citizens to choose their
representatives in free and fair elections, (2) it conducts policies that foster economic
and social development and (3) it has the capacity to maintain order and the rule of law,
and otherwise respects human rights and the democratic rules of the game (Linde and
Ekman 2003). In other words, a responsive democracy is more than constitutionally guaranteed rights and freedoms; it is a system that is built on a record of system outputs and
an acknowledged regime performance (Wagner et al. 2009). In this article, we aim to
measure this output side of the political system. We are interested in the determinants of
individuals’ satisfaction with democracy across a number of European countries. In light
of the declining trust in democracy in Western nations over the past decades (see Pharr
and Putnam 2000) and owing to the fact that there are huge differences between European
countries in satisfaction with democracy rates (see Wagner et al. 2009), it is important to
investigate both the micro-level and macro-level determinants of citizens’ satisfaction
with their democratic system.
We hypothesize that citizens’ satisfaction with democracy hinges not only on economic
factors such as economic development, but also on the quality of government services.
An essential performance indicator is the degree of corruption. Does high corruption negatively influence citizens’ satisfaction with democracy and, if so, are personal encounters/
perceptions of small-scale corruption or macro-level trends affecting individuals’ judgment of their democratic system? Answering these questions is essential for two veins of
research, the corruption literature and democracy satisfaction literature. The former (e.g.
Mauro 1995; Rothstein 2005; Stockemer et al. 2013) has predominantly analysed corruption’s influence on a host of democratic and social phenomena such as economic growth,
the social welfare state or electoral participation. The latter body of research (e.g. Anderson and Guillory 1997; Aarts and Thomassen 2008), while discussing the determinants of
citizens’ satisfaction with democracy, has only recently started to discuss the link between
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levels of corruption and citizens’ satisfaction with democracy. Hence, there is little work
that bridges these two literatures.
We add to the few existing studies (e.g. Anderson and Tverdova 2003; Dahlberg and
Holmberg 2013) by investigating the impact of large-scale indicators of corruption and
individual perceptions of corruption on individuals’ satisfaction with democracy. Analysing data from the European Social Survey (2010), covering approximately 30,000
citizens in 26 countries, we construct a multi-level model with both individual-level and
national-level control variables. It is our aim to assess the relative impact of individual
perceptions of corruption and macro-level indicators of corruption on citizens’ assessments on how democracy works in their country. Our result indicates that it is individual
perceptions of small-scale corruption that affect citizens’ satisfaction with their regime
rather than macro-level indicators of aggregate levels of corruption.
The article proceeds as follows: the next section first discusses the existing studies on
corruption and satisfaction with democracy and then introduces the handful of analyses
that have tried to bridge these two literatures. Subsequently, we describe the design of this
study, present our micro-level and macro-level control variables and explain the methodological procedures which we adopt for this research. Next, we present the results of
our hierarchical model. Finally, we discuss our findings and outline questions for future
research in the concluding section.
2 Existing literature
In this review of the relevant literature, we first present the corruption literature, followed
by the literature on satisfaction with democracy. In a third step, we then introduce the
comparatively few studies that evaluate the relationship between corruption and citizens’
satisfaction with democracy.
2.1 The corruption literature
Nowadays, there is a consensus in the literature on the widespread negative impacts from
corruption on the economic and social well-being of countries (e.g. Mauro 1995). In both
democratic and autocratic regimes, corruption hampers both sustainable development and
economic growth (e.g. Podobnik et al. 2008). For instance, if taxes are circumvented by
bribes, it deprives government of much-needed tax revenue. Furthermore, if projects go
to the payer of the highest bribe instead of to the least costly and most efficient bidder,
it bloats the costs for infrastructure projects and slows down investments (Gupta et al.
2002; Fisman and Svensson 2000). In the social realm, corruption hinders officials in
their efforts to fairly deliver public services and goods. Even worse, in a corrupt society
bureaucrats and officials frequently redirect resources and money to which the population
is entitled away from the population and into their own pockets (Warren 2004).
The literature further maintains that corruption is a sticky phenomenon that is likely
to expand to the whole society once it has taken root in the economic or political sphere
(Rothstein 2011). For example, if competitors pay or take bribes, companies in the private
realm are forced to engage in the same behaviour to gain contracts (Rothstein 2005). In
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a similar vein, it is rational for every public official to accept bribes, if he or she knows
that his or her colleagues engage in the same behaviour (Myrdal 1968, p. 409). This logic
predicts that once corruption has taken root honest institutions, enterprises and individuals will be forced into corrupt behaviour as well if they want to have the same benefits and
chances as their “corrupt” fellow citizens. This implies that corrupt behaviour becomes
rational and the society will be drawn into a self-reinforcing cycle of corruption (Rothstein and Stolle 2008; Persson et al. 2012).
While studies examining corruption’s effects on economic and social indicators have
existed for decades (Nye 1967; Huntington 1968), research has only relatively recently
started to look at how corruption impacts the democratic legacy of states. This research
has both a normative and an empirical dimension. The normative standpoint is well summarized by Warren (forthcoming) who argues that: “corruption undermines the powers
of voting and speaking that people can use to influence collective decisions—the very
powers that define democracy. It removes public contestation into non-public channels
of influence” (p. 7).
Mainly supporting Warren’s (forthcoming) normative statement, scholars have systematically examined corruption’s (negative) impact on a range of features associated
with a functioning democracy. For instance, one body of research has shown that corruption undermines participation in the political process, which is an essential part of a
thriving democracy (e.g. Karahan et al. 2006; Kostadinova 2009). To underline this point,
Stockemer et al. (2013) find that turnout is up to 10 points higher in transparent countries
as compared to corrupt countries. This implies that in corrupt jurisdiction and countries
citizens might stop seeing elections as democratic mechanisms which are worth their
effort and time (Powell 2000; Sundström and Stockemer 2013). This, in turn, could entice
politicians to become even more corrupt because they are unlikely to be punished in the
polls, if disgruntled citizens stop participating in the democratic process (Heidenheimer
Johnston 2002, p. 142).
Another, albeit related, body of scholarly work argues that perceptions of government
effectiveness—a concept which includes the absence of corruption—is crucial in making
citizens willing to obey government regulations (Levi and Sachs 2009; Levi et al. 2009;
Gilley 2009). Other studies (Wagner et al. 2009) report that corruption decreases interactions between citizens and elected officials. For example, Anderson and Tverdova (2003)
report that the existence of corruption in the political realm increases citizens’ scepticism
vis à vis public officials, regardless of whether they are guilty or not. What is implicit in
the argument that corruption decreases political engagement is the assumption that corrupt practices undermine citizens’ confidence in the democratic institutions and practices
and might compromise the legacy of the democratic system (Mishler and Rose 2001;
Seligson 2002). We follow this conjecture by evaluating the degree to which corruption
decreases citizens’ satisfaction with democracy. However, before doing so, we will present the literature on democratic satisfaction highlighting the still relatively few studies
that have empirically evaluated the link between the two concepts.
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2.2 The satisfaction with democracy literature
Studies evaluating citizens’ satisfaction with democracy are part of a larger literature
that evaluates regime support (Weitz-Shapiro 2008). Although scholars debate what the
variable “citizens’ satisfaction with democracy” really means (see Canache et al. 2001;
Anderson 2002), this concept is widely used in the literature. Referring to the concept’s
meaning, we concur with Linde and Ekman (2003), who state that: “‘satisfaction with the
way democracy works’ is not an indicator of system legitimacy per se. Rather, it is one
indicator of support for the performance of a democratic regime” (p. 401).
There is also a growing body of research that discusses the determinants of citizens’
satisfaction with democracy. For instance, Anderson and Guillory (1997) analyse the
impact of institutions on citizens’ satisfaction with democracy in consensual and majoritarian systems. Their findings indicate that losers of democratic competition are generally less satisfied; this applies, in particularly, to majoritarian systems. Karp et al (2003)
study how political knowledge affects European inhabitants’ evaluation of how satisfied
they are with their democracy. They report that individuals with high political knowledge
are less likely to be dissatisfied with the way democracy works in the EU. Aarts and
Thomassen (2008) illustrate that people who feel more represented by politicians are also
more satisfied with the performance of their regime type. Moreover, Blais and Gélineau
(2007) explore the effect of becoming a “winner” after an election—that is getting the
party you voted for in government—on satisfaction with democracy. Using panel data
from Canada, they find a positive relationship between voting for the winning party and
satisfaction with democracy. In addition, an emerging literature has increasingly started
to look at the specific linkage between corruption and satisfaction with democracy (see
Pharr 2000; della Porta 2000). We will present this literature in the upcoming section.
2.3 Corruption and satisfaction with democracy
Despite the fact that, for a long time, the literature has recognized that the regime performance affects how the public thinks about democracy (e.g. Easton 1965, 1975), comparatively few studies have evaluated the relationship between corruption and citizens’
evaluation of democratic performance. In fact, it was not until the mid-2000s that scholars
theoretically linked the concept of corruption with citizens’ evaluations with their democratic system. For example, Gilley (2006) notes that regime legitimacy is created by citizens’ evaluation of how states perform. He states that “general governance (a composite
of the rule of law, control of corruption and government effectiveness) has a large, even
overarching importance in global citizen evaluations of states” (Gilley 2006, p. 57). Three
years later, Booth and Seligson (2009, p. 220) argue that “when citizens have to bribe a
mail clerk to get a package, give a ‘tip’ to a venal teacher to assure decent attention to
their kids in school, or map a ‘fine’ to a traffic cop for some illusory infraction, they lose
respect for democracy”. Moreover, these two scholars state that “among the fundamental
premises of democratic governance are the rule of law and the notion that citizens are
legally equal and entitled to equal legal protection. To encounter government corruption
is to undergo a corrosive and disappointing experience that undermines these principles
of equitable treatment” (p. 207). In addition, Rothstein (2009) develops the reasoning
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for why people’s legitimacy of the political system is dependent on how well the system
functions. He argues
It is the absence of corruption, discrimination, and similar violations of the principle
of impartiality in exercising political power that serves to create political legitimacy.
The manner in which public administrations are organized is not just a question
of economic rationality and administrative efficiency. In addition, citizens seem to
have strong norms about what to expect when they encounter government officials
that implement public policies… One could say that the public administration is the
political system—as citizens concretely encounter and experience it. The character
of the administration, therefore, is decisive for the way in which the political system
is viewed. (Rothstein 2009, p. 325)
Building and sometimes even preceding this theoretical reasoning, there are several
empirical studies that directly analyse the influence of corruption on citizens’ satisfaction with their state’s democracy. The majority of these few studies find that corruption
hampers individuals’ satisfaction with their country’s regime. For example, Anderson and
Tverdova (2003) analyse data from the International Social Survey Program, consisting
of individual-level perceptions on satisfaction with the performance of the system and
trust in civil servants in 16 new and old democracies. Focusing on corruption, measured
by the Corruption Perception Index (1996), they find that citizens in corrupt democracies are less satisfied with the performance of their system and have less trust in public officials compared to citizens in less corrupt societies. Similar results are reported
in a study by Wagner et al. (2009). The authors investigate the impact of institutional
quality on satisfaction with democracy in a longitudinal research design, utilizing data
from the Eurobarometer Survey over the years 1990–2000. Their results indicate find that
low corruption and a functioning rule of law have a positive impact on satisfaction with
democracy.
Other researchers (e.g. Norris 2012) have refined their research design and focus on
the relative impact of corruption and good governance in comparison to other factors,
which are also likely to influence citizens’ evaluation of their regime. Most pronouncedly,
Rothstein (2009) proposes that the quality of government—a concept that he defines by
the degree of partiality and corruption in government services—is relatively more important than constitutional arrangement to create regime support. This result has spurred
some recent research re-investigating this claim empirically. For example, Dahlberg
and Holmberg (2013) analyse individual data from the Comparative Study of Election
Systems survey in 32 democracies and report that citizens’ evaluations of government
performance (such as an impartial bureaucracy relatively free of corruption) have a substantially stronger impact on individual satisfaction with how democracy works than do
measures on citizens’ ideological congruence with national politicians. In another study,
Dahlberg et al. (2013) come to slightly different conclusions. They investigate the factors
which affect individuals’ likelihood of being a “satisfied” or a “dissatisfied” democrat
in a range of countries and evaluate whether subjective measures of being represented
by politicians have a stronger influence on citizens’ perceptions with democracy than
opinions of government performance. Interestingly, they find that corruption has a negative effect on citizens’ satisfaction score in newly democratized countries but not in older
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ones. This point of view is somewhat countered by Gjefsen (2012), whose study clearly
indicates that it is regime performance rather than the process of electoral democracy that
matters for citizens’ satisfaction with their regime.
There are also some, albeit few studies which look at the constituents of government
performance in settings outside the more developed democracies. For example, Chang
and Chu (2006) find a rather weak link between corruption and institutional trust in Asia.
Investigating the impact of corruption on citizens’ trust in political institutions in five
democracies in Asia these two scholars find that corruption is not strongly associated
with citizens’ satisfaction with democracy. Several other studies from countries outside
of Europe, however, find strong effects of corruption on citizens’ satisfaction with democracy. Analysing citizens’ satisfaction with democracy in a number of African countries
with Afrobarometer survey data from three rounds, in 2000, 2002 and in 2005 Bratton
(2007) reports that individual perceptions of widespread corruption in the political sphere
have a negative impact on an individual’s likelihood to support the democratic system.
However, others have found that while corruption negatively affects the evaluations
of the performance of democracies it does not necessarily affect the individual support
for the principles of democracy. For instance, Canache and Allison (2005) analyse World
Values Survey data from several Latin American countries from the years 1995–1997 and
report that perceptions of corruption exert a negative effect on support for the incumbent
government and the current political system. However, they do not find any significant
association between perceptions of corruption and support for democratic principles.
The authors therefore conclude that citizens make a critical evaluation and can distinguish between existing democratic institutions and democracy as a form of government
(p. 106). Booth and Seligson (2009, p. 142) report similar findings in their analysis of attitudinal data from the AmericasBarometer survey in eight Latin American countries. Their
results indicate that while the experience of having paid a bribe negatively affects the
support for certain institutions, incumbents and local governments, this does not undermine the backing of democratic principles among the Latin American respondents. These
findings stand in slight contrast to a study by Weitz-Shapiro (2008) which was conducted
in Latin America. The article reports that getting bad services is not sufficient to affect
citizens’ satisfaction with democracy in Argentina. However, the author finds that the
perception of having a corrupt government affects citizens’ evaluations of their democracy and affects the support of the principles of democracy. According to her “certain
measures of local government performance, such as corruption, have ramifications for
citizens’ evaluations of the functioning of their democracy and even for citizens’ faith in
democracy per se” (p. 285).
Taken together, there is some rather solid evidence that corruption decreases citizens’
satisfaction with their democratic system. However, there are still a host of research questions that need further exploration. First, studies (Gjefsen 2012; Dahlberg et al. 2013)
have just started to look at the relative influence of corruption on citizens’ satisfaction
with democracy with regard to other factors such as economic performance, constitutional
mechanisms and policy representation of citizens. Secondly, a focal point in this article, the
literature has so far not distinguished between the effects of different types of corruption on
satisfaction with democracy. In the next section we further define these variants of corruption. We then proceed to state our theoretical expectations and pose our research questions.
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3 Defining corruption and satisfaction with democracy
Traditionally, corruption is defined as “the misuse of public power for private gain” (Treisman 2007). The concept is naturally complex and its definition has been challenged
and amended (see Johnston 1996; Warren forthcoming). For instance, international anticorruption watchdog Transparency International (TI) argues that the definition “the abuse
of entrusted power for private gain” is more accurate as it also includes abuse of power in
bodies outside the state (TI 2013). Nonetheless, the basic notion we aim to capture when
discussing corruption is the abuse or misuse of power for private gain. This abuse or misuse of power may take various shapes; it may be from bureaucrats asking for small bribes
(monetary as well as non-monetary) when delivering public goods, as well as politicians
receiving huge amounts of money or non-monetary benefits to alter the decision-making
process. This mirrors the often-made distinction of two types of corruption: petty and
grand corruption (e.g. Wilson and Damania 2005).
When speaking of petty corruption, we also refer to small-scale corruption among
public officials, e.g. bribery for a faster delivery of a public service. Grand corruption
refers to large-scale corruption involving politically elected decision-makers during the
shaping of policy (Hellman et al. 2000). Moreover, corruption may also vary in in that it
can affect different sectors of society and, equally importantly, its magnitude may vary,
ranging from occasional instances to outright state-capture where corruption is endemic
to the system (Johnston 2005). Referring to the distinction between petty and grand types
of corruption—where the former denotes small-scale corruption among public servants
during the implementation of policy and the latter denotes large-scale corruption involving decision-makers during the formulation of policy—we will explore a potentially
interesting difference. Is it small-scale or grand corruption that affects citizens’ satisfaction with democracy? For example, Uslaner (2008) posits that while grand corruption
affects trust in government petty corruption does not. However, his study deals with trust
in government institutions. In contrast, we want to disentangle if a similar pattern holds
for individuals’ satisfaction with democracy as the dependent variable. Given the limitations in the availability of existing data, our aim is to investigate the differences between
individual perceptions of petty types of corruption and indicators of broad macro-level
trends of corruption in an aggregate.
With regards to satisfaction with democracy, the concept has been used as both an
ideal set of principles (i.e. democracy as the best form of government) but also an existing
mode of government (i.e. how satisfied individuals are with their government) (WeitzShapiro 2008). In reality these two aspects of political support most likely affect each
other (Easton 1975). For instance, a long or intense period of misconduct within a democratic regime might affect citizens’ evaluations of support for democracy, not only how it
works in practice, but also their perceptions of the principles of this mode of governance
as such (Weitz-Shapiro 2008, p. 288). Although the concept of political support arguably
may include both these categories, the concept of satisfaction with democracy implies an
evaluation of the current system. We therefore use the discussion by Linde and Ekman
(2003) as a basis, and argue that the variable—satisfaction with democracy—is not an
indicator of support for the principles of democracy, but rather an item that taps the level
of support for the way a democratic regime works in practice (p. 391). When we use this
Corruption and citizens’ satisfaction with democracy in Europe …
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concept we therefore refer to citizens’ evaluations of how the democratic regime is exercised rather than how much they normatively support democracy.
We ask the following research question: Is it petty or grand-scale corruption that influences citizens’ satisfaction with democracy? To answer this query we evaluate the impact
of both micro-level and macro-level indicators of corruption across a broad sample of 26
European democracies. Adding relevant individual and contextual control variables will
show us the absolute and relative influence of both corruption indicators on an individual’s appraisal of his or her country’s democratic performance. In the next section we will
operationalize our main variables of interest, as well as introducing the micro-level and
macro-level control variables that are also likely to influence how satisfied an individual
is with democracy in his or her country.
4 Operationalizations and control variables
4.1 Dependent variable—satisfaction with democracy
As the dependent variable, we use the following question for participants: “How satisfied are you with the way democracy works in your country?” The answer is given on an
11-point scale ranging from extremely dissatisfied (coded 0) to extremely satisfied (coded
10). We retrieved this dependent variable, as well as all the other micro-level indicators,
from the most recent wave of the European Social Survey, which was conducted in the
year 2010.
4.2 Independent variable corruption
We measure our main independent variable, corruption, with the help of two micro-level
indicators and one macro-level variable. The two survey items we include as proxies for
small-scale corruption ask individuals how much they think that judges and police in
their country accept bribes. These two items, which range from 0 (never) to 10 (always),
respectively, should capture individuals’ evaluations of the degree to which they think
that petty corruption is present in the judicial system and police. To gauge another dimension of corruption, macro-level corruption trends, we use the World Bank Control of
Corruption Indicator (Kaufmann et al. 2005). The indicator is a standardized measure of
national-level figures with a mean of 0 and a range between − 2.5 and 2.5.1 It is constructed
with the help of various data sources from different organizations (i.e. data from countries’ statistical offices, the World Bank, Transparency International etc.). This implies
that countries for which lots of data exists have “more accurate” scores than developing
or third world countries that sometimes do not even have a statistical office (Knack 2006).
However, since basically all countries that are part of our dataset are economically developed countries, we can assume that the quality of the data for the sample at hand is high.
1 We inversed the original coding from the World Bank to render the interpretation of the data
more tangible. High values on the indicator mean high corruption now and low values low corruption.
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However, we must note that our macro-level measure of corruption gauges both petty and
grand corruption in a country and thus is a contextual measure of corruption rather than
an indicator of grand corruption per se. In this sense, this indicator captures “perceptions
of the extent to which public power is exercised for private gain, including both petty and
grand forms of corruption, as well as “capture” of the state by elites and private interests”
(The World Bank 2013a). However it does so on the macro-level gauging how strongly
corruption is endemic in the system, as compared to individuals’ personal encounters with
corrupt practices. Hence, we deem this indicator appropriate for our purpose.
While it is the main goal of this research to test the relative influence of individual perceptions of corruption and macro-level trends on citizens’ satisfaction with democracy,
we have to control for relevant individual and contextual factors which might also influence an individual’s evaluations of democracy in his or her country.
4.3 Micro-level control variables
We hypothesize that, on the individual level, the performance of the government to deliver
economic affluence, public goods and security should directly influence citizens’ satisfaction with how democracy works in their country (e.g. Waldron-Moore 1999; Schäfer
2010). For example, Bäck and Kestilä (2009) find that individuals who report that they
are member of a group that is discriminated in a given country are less satisfied with
democracy than citizens that feel to be full citizens of this country. They also report that
economic well-being and high quality public services can predict democracy satisfaction
(p. 189). To gauge these individual aspects we therefore control for a citizen’s satisfaction with the economy, government and the education system, whether an individual participates in social activities, whether he or she feels safe in walking alone at night and
whether the person feels discriminated against.
Moreover we address the impact of socio-economic variables. Income is generally
found to be an important predictor at the individual level, where more affluent citizens
tend to report a higher satisfaction with democracy (e.g. Gulbrandtsen and Skaning 2010;
Wells and Krieckhaus 2006; Blais and Gélineau 2007; Schäfer 2010). For our next two
indicators, the results are more mixed. While some studies (e.g. Anderson and Tverdova
2003; Curini 2010) find positive effects of higher education and male gender on satisfaction with democracy, other studies report mixed results in this aspect (e.g. Gulbrandtsen
and Skaning 2010; Wells and Krieckhaus 2006; Blais and Gélineau 2007). Age is a significant predictor in some studies (i.e. older individuals show higher satisfaction; e.g.
Dahlberg and Holmberg 2013), but remains insignificant in others (Anderson and Tverdova 2003; Curini 2010). To control for these to date conflicting yet potentially important
aspects, we control for gender, age, education and income.
The first three micro-level variables, which measure people’s satisfaction with the
economy, the government, and the education system, range from 0 (extremely dissatisfied) to 10 (extremely satisfied). The fourth indicator, which asks individuals how much
they take part in social activities compared to others of the same age, is a 5-point ordinal
variable with values from 1 (much less than others) to 5 (much more than others). The
fifth variable, which probes respondents about whether or not they feel safe walking home
at night, has 4 categories (i.e. from very safe coded 1 to very unsafe coded 4). The sixth
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factor, which is derived from the question whether individuals feel discriminated against
or not, is a dummy variable coded 1 for individuals who feel discriminated against and 0
otherwise. The final four demographic factors are coded as follows: gender is a dummy
variable coded 1 for men and 0 for women, age measures respondents’ age in years at the
time the survey was conducted (i.e. in 2010), education is a ordinal variable coded 1 for
higher secondary education or lower to 7 for the Master’s level or higher and income is a
standardized variable that measures individuals’ income on a 10-point scale from 1 (low
income) to 10 (high income).
4.4 Macro-level control variables
Perceptions of democratic performance are influenced not only by individuals’ specific
experiences but also by larger trends in society, or as Anderson (2007) puts it, “the macro
contexts in which citizens find themselves” (p. 592). First, we follow prior research and
hypothesize that macro-level economic performance is important for citizens’ evaluation of the democracy (e.g. Waldron-Moore 1999; Schäfer 2010). Second, we control
for economic inequality. Pertaining to this factor, Anderson and Singer (2008) find that
macro-level variables of inequality predict individual trust in public institutions as well
their satisfaction with how the democracy works. Four years later, Schäfer (2012) corroborates Anderson’s and Singer’s (2008) finding and reports that high income inequality makes individuals less satisfied with the way the democracy works in their country.
Third, studies (Andersson 2002; Gulbrandtsen and Skaning 2010; Curini 2010) also point
to the important differences between older and new democracies, where individuals in
consolidated democracies have an overall higher satisfaction level with democracy than
individuals in newly democratized countries. On the national level, we therefore control
for development, economic growth, democratic stock, and income inequalities. More specifically, we assume that higher levels of economic development and economic growth,
lower degrees of economic inequality and longer years of democratic rule will have a
positive impact on citizens’ satisfaction with how democracy works in their country.
The four macro-level control variables are operationalized as follows: (1) the development indicator is gauged in its standard way, namely by a country’s GDP per capita in
current US dollars. The data were retrieved from the World Bank (2013b). Because of a
hypothesized non-linear relationship between material wealth and citizens’ satisfaction
with democracy we log transform the variable GDP per capita. (2) Economic growth is
measured by the annual growth rate in a country’s GDP per capita. The data also come
from the World Bank (2013c). The second-to-last control variable, income inequality, is
operationalized by the Gini coefficient. Our Gini data are from the SWIID dataset (version 3.1) developed by Solt (2009). The final measure, democratic stock, gauges the years
a country has been a democracy without interruption. Data for this last variable are from
PolityIV (2012) (see Jaggers and Gurr 1995).
148
D. Stockemer and A. Sundström
5 Methodology
To gauge the influence of individually perceived small-scale corruption and macro-level
indicators of corruption trends on an individual’s satisfaction of democracy in his or her
country, we have retrieved data for 29,865 individuals in 26 European countries.2 There
is wide variation in our dependent variable, individuals’ satisfaction with democracy. For
example, individuals in Greece and Ukraine are rather dissatisfied with how well democracy functions in their country (i.e. they give a mean satisfaction rating of 3), whereas
citizens in Norway or the Netherlands are rather satisfied (on average, they give a 7 out
of 10 in their satisfaction with democracy rating). We find the same wide variation for our
two individual corruption measures. In nearly all countries, people use the whole range of
answers (i.e. they choose answers from 0 to 10 in their evaluation on whether the police
and the judges are corrupt). The spread in our macro-level corruption indicator is a little
more nuanced. While many of the Northern and Western European countries (e.g. Norway, Sweden, the Netherlands or Switzerland) are champions in the fight of corruption,
others in South or East Europe are in the medium tier worldwide (i.e. Greece) or even in
the lower third (e.g. Russia and Ukraine) (see descriptive statistics of all variables in the
appendix).
To ensure that our two dimensions of corruption, micro-level and macro-level corruption are distinct, we run a correlation matrix between our two micro-level corruption
indicators and our macro-level variable. We find that the correlation coefficient between
the two micro-level factors and the macro-level factors is around 0.53 (0.53 between individual perceptions of policy corruption and the WB corruption indicator and 0.54 for the
indicator whether citizens perceive judges to be corrupt and the WB corruption indicator).
While this moderately strong correlation coefficient indicates that macro-level corruption
trends and individual perceptions of corruption are related, it also shows that individuals’
opinions on how corrupt institutions are can differ quite fundamentally from macro-level
trends or expert opinions. This applies even more if we consider the high standard deviation in perceptions of corruptions in all countries (i.e. the standard deviation in both petty
corruption indicators is above 2, given a range of 11, which is pretty significant).
To gauge the influence of individual micro-level perceptions of corruption and macrolevel trends on individual satisfaction with democracy ratings, we engage in a two-step
process. First we provide some graphical representations of the relationship between our
two individual corruption indicators and our macro-level corruption indicator on the one
hand, and our dependent variable satisfaction with democracy on the other hand. Second, and to have some more robust evidence of the relationship between various form
of corruption and individuals’ assessment of the procedural quality of democracy, we
use multi-level modelling.3 We have data that span two levels. On the individual level
2 The countries included in this analysis are: Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Israel, Lithuania,
Norway, Poland, Portugal, Russia, Spain, Switzerland, The Netherlands, Sweden, Slovenia,
Slovakia, Ukraine.
3 OLS models or transformations of OLS models are inappropriate for hierarchical data, because
they cannot account for the two-level data structure (Wells and Krieckhaus 2006).
Corruption and citizens’ satisfaction with democracy in Europe …
149
we are interested in how citizens’ perceptions of small-scale corruption as well as our
ten micro-level control variables influence an individual’s evaluation of democracy in
his or her country. However, every individual lives in a distinct national context, which
might also influence his or her evaluation of the democratic system. Hierarchical Linear
Modelling (HLM) allows us to model this two-level structure of the data (Guldbrandsen
and Skaning 2010, pp. 170–171). More precisely, HLM properly accounts for the fact
that the individual data is clustered within its national context. Directly measuring these
macro-level factors’ influence on a citizen’s evaluation of how democracy works avoids
an over-estimation of the statistical significance of the micro-level coefficient estimates.
This, in turn, allows for a better depiction of the micro-level variables’ impact on individual satisfaction with democracy ratings (O’Connell and McCoach 2008).
6 Results
Figure 1 displays the bivariate relationship between citizens’ perceptions on whether the
police (red line) or the judges (blue line) are corrupted, on the one hand, and satisfaction
with democracy on the other hand. The y-axis displays our dependent variable citizens’
satisfaction with democracy and the x-axis individuals’ evaluations of the level of corruption in the police forces and among judges (e.g. higher values signify higher satisfaction
with democracy and more corruption, respectively). Both fitted regression lines are statistically significant, indicating that individuals who perceive that policemen and judges are
more corrupt are less satisfied with how democracy works in their country than individuals who do not think that either of the two institutions are corrupted. Substantively, the
two fitted lines indicate a more than 3-point gap in citizens’ appraisal of their democracy
between those who think that both institutions are very transparent and those who think
that both institutions are corrupted.
Figure 2 shows the association between our macro-corruption indicator on the x-axis
and average scores of citizens’ satisfaction with democracy per country on the y-axes.
6DWLVIDFWLRQZLWK'HPRFUDF\
Fig. 1: The influence of microlevel corruption perceptions on
individuals’ evaluation of their
democracy
3HUFHSWLRQVRI0LFUROHYHOVRIFRUUXSWLRQ
150
6DWLVIDFWLRQZLWK'HPRFUDF\
Fig. 2: The influence of macro-level corruption trends on
aggregate levels of citizens’ satisfaction with their democracy
D. Stockemer and A. Sundström
:%&RUUXSWLRQ
Relatively unsurprisingly, the fitted regression line mirrors the results in Fig. 1, illustrating that countries’ that suffer from higher macro-levels of corruption, have, in the
aggregate, fewer citizens that are content with the way democracy works in their country.
However, what is still unclear is whether these overall corruption trends directly influence citizens’ evaluations of how they think procedural democracy works in their country.
Only a hierarchical linear model can determine whether it is individual perceptions or
encounters with macro-corruption that matter in citizens’ evaluations of their satisfaction
with democracy in their country. The next section will engage in this endeavour.
Table 1 displays the results of our HLM model. Our two-level model illustrates that
both micro-level factors of corruption are negatively related to citizens’ evaluation of
their regime performance in a statistically significant and substantively meaningful manner. More precisely, the two variables decrease individuals’ satisfaction with their democracy by up to 0.4 points for their evaluation on whether police accepts bribes and up to 0.7
for their evaluation on whether judges take bribes. This finding also implies that citizens’
perception of whether judges are corrupt has a more detrimental impact on individuals’
assessment of the quality of democracy than the perception that policemen and policewomen are corrupt. In contrast, we do not find any relationship between the macro-level
indicator of corruption and individuals’ satisfaction with their democracy. The indicator
is not statistically significant and its substantive influence is negligible. This implies that
individuals judge their system by their own perceptions of corruption and not by certain
macro-trends.
Pertaining to the control variables, we find that, except for age and gender, all our
micro-level control variables have the expected sign and are statistically significant. Our
results indicate that an individual’s satisfaction with democracy is first and foremost
driven by his or her assessment of the government and the economy, as well as his or
her education. The first of the three variables influences citizens’ satisfaction ratings with
democracy by up to 4 % points, which is considerable given a range of the dependent
variable of 11. The second and third indicator, an individual’s assessment of the economy and an individual’s educational attainment, have a somewhat smaller impact, but
Corruption and citizens’ satisfaction with democracy in Europe …
Table 1: Results of the HLM model
Fixed effects
Coefficient (SE)
t
(df)
Model of an individual’s mean democracy’s satisfaction score (β0)
Intercept (γ00)
1.31
(0.51)
2.57
(20)
Corruption (γ01)
(0.13)
0.436
(20)
− 0.0658
GDP per capita (γ02)
0.000011
(0.000006)
1.87
(20)
Economic growth (γ03)
(0.022)
(20)
− 0.017
− 0.793
Gini coefficient (γ04)
0.0058
(0.017)
0.334
(20)
Years democracy (γ05)
(0.020)
(20)
− 0.0021
− 1.10
Model on an individual’s evaluation on whether police takes bribes slope (β1)
Intercept (y10)
(0.008)
(29851)
− 0.040
− 5.28
Model on an individual’s evaluation on whether judges take bribes slope (β2)
Intercept (y20)
(0.010)
(29851)
− 0.070
− 7.06
Model on an individual’s satisfaction with the government slope (β3)
Intercept (y30)
0.42
(0.013)
30.82
(29851)
Model on an individual’s satisfaction with the economy slope (β4)
Intercept (y40)
0.17
(0.015)
10.83
(29851)
Model on an individual’s satisfaction with the educational system slope (β5)
Intercept (y50)
0.21
(0.014)
15.21
(29851)
Model on an individual taking part in social activities slope (β6)
Intercept (y60)
0.039
(0.013)
2.93
(29851)
Model on an individual feeling safe (β7)
Intercept (y70)
(0.021)
(29851)
− 0.088
− 4.21
Model on an individual feeling discriminated against (β8)
Intercept (y80)
(0.065)
(29851)
− 0.24
− 3.66
Model on an individual’s gender (β9)
Intercept (y90)
0.0045
(0.022)
0.210
(29851)
Model on an individual’s age (β10)
Intercept (y100)
(0.0012)
(29851)
− 0.0013
− 1.06
Model on an individual’s education (β11)
Intercept (y110)
0.050
(0.010)
4.89
(29851)
Model on an individual’s income (β12)
Intercept (y120)
0.025
(0.005)
4.75
(29851)
Random effects
Std. dev
Variance
DF
χ2
Intercept 1, u0
0.42
0.17
20
1337
Level 1, r
1.70
2.89
151
p
0.018
0.668
0.076
0.437
0.747
0.286
< 0.001
< 0.001
< 0.001
< 0.001
< 0.001
0.003
< 0.001
< 0.001
0.834
0.291
< 0.001
< 0.001
p-value
< 0.001
still influence an individual’s judgment of the regime performance by approximately 2 %
points each. The other significant variables’ influence, while still perceptible, is somewhat
weaker. None of these indicators potentially influences the dependent variable by more
than 1 % point.
In contrast to our micro-level control variables, the macro-level controls have less
of an influence on an individual’s assessment of his or her regime performance. In fact,
except for development, none of the other indicators is statistically or substantively rel-
152
D. Stockemer and A. Sundström
evant. Even the GDP per capita variable is only significant at the 10 % level (p = 0.078)
and its substantive influence is moderate. The model predicts that for every 10,000 dollar
the GDP per capita of a country increases satisfaction ratings with democracy increase by
approximately 1 % point, which is a rather moderate increase. More generally, this lack of
strong linkages of macro-level factors on individuals’ evaluations of regime satisfaction
allows for the (tentative) conclusion that it is not context that impacts individual opinions
on democracy but rather the perception of personal realities in individual lives.
Returning to our main variable of influence, perceptions of corruption, we find that
both individual proxy variables of corruption have a moderate influence on individuals’
perception of the quality of democracy in their country. However, these two proxy variables only measure the direct influence of corruption on assessments of regime performance. There is almost certainly also an indirect influence. Prior research (e.g. Rothstein
2003; Warren 2004) has shown that if corruption is widespread, the economy functions
poorly, governments are dysfunctional and the education system does not promote the
best minds, but rather those who pay the highest bribes. Hence, it is likely that corruption
not only influences how satisfied citizens are with their democracy, but most likely also
individuals’ assessment of the economy, government and education sector. Moreover,
corruption in the police and the judicial sector could potentially compromise individuals’
perceptions of public safety and their assessment of whether or not they are discriminated
against. All in all, these conjectures imply that perceptions of petty types of corruption
could strongly influence individuals’ personal lives. Future research should investigate
these indirect links. A propitious way to do so would be the construction of a structural
equation model, which allows researchers to measure the direct and indirect paths of corruption on citizens’ evaluations of their democracy.
7 Conclusion
The contribution of this article is twofold. First, our article nicely complements the few
existing studies (e.g. Anderson and Tverdova 2003; Dahlberg et al. 2013) that empirically
test the link between corruption and perceptions of satisfaction with democracy. Finding
support for the stipulation that if people perceive the police or/and the judges as corrupt,
they will be less satisfied with their regime, our study not only illustrates another negative
consequence of corruption, but also cautions future work to include these factors in models gauging the constituents of individual evaluations of regime performance. Second,
our research sheds some light on the type of corruption that influences citizens’ opinions.
We find that macro-level corruption trends are a good predictor of aggregate satisfaction
with democracy ratings. However, these macro-trends are rather irrelevant for individuals’ assessment of the performance of democracy. Rather than overall corruption, it is
citizens’ personal perceptions of petty corruption that impacts their regime evaluations.
While we have pushed the research on corruption and people’s assessment of democracy further, our research opens up several more research questions. First, to confirm
that only individuals’ perceptions of corruption and no macro-corruption trends influence
individuals’ satisfaction with democracy, future research could redo the same study using
more countries from different regions. This would allow researchers to have even more
Corruption and citizens’ satisfaction with democracy in Europe …
153
variation on both macro-level corruption trends and citizens’ satisfaction with democracy.
Second and as already mentioned, future research should disentangle the direct and indirect effects of perceptions of corruption on perceptions of the functioning of the regime.
Third, large-scale surveys (e.g. the European Social Survey or the World Value Survey)
could include more corruption questions to further evaluate the sectors where corruption
is most detrimental in citizens’ minds. For example, these surveys could include a direct
question on whether politicians are corrupt, in order to gauge aspects of grand corruption.
Despite the fact that we have asked more questions than we have provided answers, we
still hope that the current study advances our knowledge on the (negative) consequences
of corruption as well as the indicators that drive individuals’ opinions of their regime
(Table 2 and 3).
Appendix: Descriptive statistics
Table 2: Micro-level indicators
Variable name
Satisfaction with democracy
Perception police accepts bribes
Perception judges accept bribes
Satisfaction with government
Satisfaction with education
Participation in social activities
Feeling of safety
Feeling discriminated against
Gender
Age
Education
Income
Table 3: Macro-level indicators
Variable name
Corruption
GDP per capita
Economic growth
Gini coefficient
Years democracy
Mean
5.02
4.02
3.73
4.23
5.51
2.75
2
0.06
0.48
47.75
3.98
5.34
Mean
− 0.96
34431
2.11
29.62
5.51
Standard deviation
2.54
2.67
3.73
2.53
2.36
0.93
0.8
0.24
0.5
17.61
1.82
2.77
Minimum
0
0
0
0
0
1
1
0
0
14
0
1
Maximum
10
10
10
10
10
5
4
1
1
101
7
10
Standard deviation
− 0.99
23196
2.77
5.34
2.36
Minimum
− 2.42
3615
− 7.10
21.92
0
Maximum
1.09
98102
8.30
45.24
175
154
D. Stockemer and A. Sundström
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