This chapter makes use of the EVS longitudinal integrated file to analyse whether an overall trend towards higher income inequality is associated with growing or declining acceptance of corrupt acts among different social strata. Taking advantage of innovations in multilevel modelling allowed for by the ‘repeated cross-sectional’-nature of this data source, we find that contradictory findings established in previous studies are hard to replicate: there is no relationship between the ‘average’ level (between countries) or the changes (within countries) in income inequality and the acceptance of corrupt acts. Further findings suggest that future research should account for so-called ‘cluster-effects’, whereby ‘families of countries’ with similar religiously-rooted institutional and legal-historical traditions and regulations, systematically vary in terms of value orientations. In particular, we find higher acceptance of corrupt acts in the Southern- and Eastern-European countries compared to the Northern countries. Future research could flesh out which macro-level institutional arrangements (e.g., religion) are associated with which micro-level social attitudes and norms related to the ‘acceptance of corruption’.
Corruption – defined as the (ab)use of public authority and/or office for private gain, large or small – is a topic of study across the social sciences. Sociologists, not surprisingly, are interested in the social causes and consequences of the level of corruption, as well as its acceptance by the general population. Regarding its social consequences, the level of corruption in a society acts as a contextual stressor leading to, for instance, lower life satisfaction (Amini, 2020) and mental illness (van Deurzen, 2017). When corruption is more abundant, people feel more concerned, powerless, and hostile towards the unfairness and injustice of their social environment. Corruption also impacts on material living conditions, by endangering access to often basic goods and services (Lambsdorff, 2006).
According to You & Khagram (2005), the level of corruption is influenced by material and normative behaviours, among which a higher tolerance of corruption as ‘acceptable behaviour’ is a key element. The authors then link the higher acceptance of corrupt acts to the level of income inequality, thus proposing a causal relationship between increasing inequality levels and increasing corruption levels through this mechanism. This argument goes against (development) economists’ focus on the detrimental impacts of corruption on efforts to achieve a more equitable (re)distribution of resources (e.g., by reducing tax revenues or the effectiveness of public spending), resulting in a ‘loss’ of economic growth, as well as higher levels of inequality (Lambsdorff, 2006). A ‘drone-like review’ of the literature reveals that reversed relationships between various forms of ‘inequality’ on the one hand, and ‘corruption’ on the other hand – in other words: “does corruption lead to higher inequality, or does higher inequality breed more corruption?” – are a proverbial ‘can of worms’.
Most studies attempt to answer these questions by modelling statistical (often cross-sectional) relationships between ‘macro-level’ indicators (e.g. the Gini-index as a measure of income inequality and the often-used ‘Corruption Perception-Index’ compiled by Transparency International) pertaining to geographically widely different samples of countries, characterized by varying levels of economic development and democracy (e.g. Policardo & Sánchez Carrera, 2018; Pop, 2012; You & Khagram, 2005). Because there is also a strong and consistent negative macro-level association between economic affluence and the level of corruption confounding relations between corruption and its social causes and consequences (van Deurzen, 2017), a pattern of contradictory and ‘entangled’ research findings arises. This is further complicated by the fact that most studies focusing on societal (macro-level) indicators put forward a host of speculative ‘underlying’ micro-level argumentations that are hardly empirically verified. In line with You & Khagram (2005), Policardo et al. (2018, p. 100), for instance, also suggest that a positive impact of income inequality on corruption1 may be explained by the fact that “when poverty is widespread and people underpaid, the incentives to pursue wealth (even in an unfair and illegal way) increase.”
Based on such arguments, it is easy to assume associations between the level of inequality and acceptance of corrupt acts. However, from a methodological perspective, comparative studies of this kind suffer from serious limitations, in the sense that inferences about social change over time are mostly derived from cross-country differences at a particular point in time. Focusing more directly on finding more robust evidence for this mechanism, i.e., that changes in income inequality are linked to changes in the level of acceptance of corrupt acts, is a first step toward settling the income inequality-corruption dispute, and the pathway that we are exploring in this chapter.
It is furthermore likely that at least part of these supposedly ‘linear’ relationships arises from so-called ‘cluster-effects’, whereby ‘families of countries’ with similar religiously-rooted institutional and legal-historical traditions and regulations, which also happen to cluster around certain levels of inequality and economic affluence, systematically vary in terms of value orientations. Even though with modernization and rationalization came secularization, religion remains an important influence in people’s lives. Numerous public and private institutions and organizations (e.g. social policy, schools, and civil society) continue to reflect the hallmarks of their religious roots. As Loek Halman repeatedly demonstrated in his work, religion hence directly and indirectly serves as a source of morality and civic engagement (De Hart, Dekker & Halman, 2013; Halman & Van Ingen, 2015). Religion is furthermore associated with variations across Europe on the dimension of normative value orientations, i.e. “the maintenance of strict moral standards and the valuing of strict social norms, institutions, and solidarity with a rejection of self-interest and illegal behaviors” (Halman & Voicu, 2010, p. 3). Regarding the focus of this chapter, a cultural-legal heritage of Protestantism (stressing individual responsibility) and British common law (focused on the preservation of private property) tend to be associated with lower levels and acceptance of corruption (You & Khagram, 2005). Halman & Voicu (2010), however, note that Catholic societies appear stricter than Protestant and Orthodox ones, although in the latter, mostly Eastern-European, countries, since the collapse of communism a religious revival has taken place.
In this explorative chapter, we contribute to the existing literature by focusing on one particular mechanism that has been put forward regarding the supposed causal impact of inequality on corruption: the acceptance of corrupt acts. To this end, we make use of advanced statistical modelling to exploit the richness and longitudinal nature of the European Values Study (EVS). We focus particularly on income inequality, given that there is a long-standing body of literature documenting, firstly, its increase since the mid-70’s across both advanced and emerging welfare democracies across the western hemisphere, following interdependent processes of economic globalization and technological change, welfare state restructuring, post-communist market transition, and changes in household formation (e.g. Alderson & Nielsen, 2002; Bandelj & Mahutga, 2010; Esping-Andersen, 2007; Heyns, 2005; Milanovic, 2016; OECD, 2015).
Secondly, a large body of literature has sought to substantiate Wilkinson and Pickett’s (2009) claim that in particular relative income inequality has harmful social consequences, through processes such as increased competition for social status or declining solidarity (e.g. Lancee & Van de Werfhorst, 2012; Paskov & Dewilde, 2012; van Deurzen, van Ingen, & van Oorschot, 2015). As “income distributions change at a glacial pace” (Heyns, 2005, p. 173), a common criticism is that most of these (cross-sectional) studies capture country-differences rather than actual change over time. As one of the most long-running surveys, the EVS, however, offers the opportunity to study the impact of changes in income inequality on changes in the acceptance of corrupt acts, for a suitably long time period, whilst taking account of both micro-level (individual) and macro-level (contextual) influences. Furthermore, the survey includes a wide range of countries, including new democracies that experienced deep social change (e.g., from communism to a free-market economy), and often-times also strong increases in income inequality, since the 1990s.
From previous research it is possible to derive competing expectations regarding the impact of changes in income inequality on the acceptance of corrupt acts. This is also reflected in the empirical evidence so far: whilst You & Khagram (2005) expect and find an ‘overall’ positive effect of income inequality on perceived corruption (mediated by a higher acceptance of corruption), Pop (2012) reports an overall negative association between income inequality and the acceptance of corrupt acts. Though the latter study includes 43 European countries (compared with 129 countries in the former), and this could explain the divergent conclusion, from a theoretical perspective the possibility exists that individuals with different social positions experience the distribution of resources in society differently and this would make corrupt behaviour more or less acceptable. In other words, higher inequality could be associated with either higher or lower acceptance of corrupt acts by different social groups in society.
One such line of argumentation links increases in inequality to increased opportunities for the rich and powerful to lead increasingly segregated lives, contributing to declining meeting opportunities with, empathy for, and solidarity with poorer people (Mijs, 2019; Paskov & Dewilde, 2012). You & Khagram (2005) furthermore argue that at higher levels of inequality, those at the high-end have more to lose through the proper functioning of ‘meritocratic’ processes, as well as possessing more resources to gain influence in order to counter-act such influences. Higher inequality will therefore be more conducive to a higher tolerance of corrupt acts among the higher social strata (H1).
But what happens with the rest of the population? Expectations become more blurry when it comes to the lower social strata. On the one hand, it could be that, especially in societies with higher inequality and less democracy, where “it is impossible to do well honestly” (You & Khagram, 2005, p. 138), corruption is a necessary ‘everyday evil’ in order to secure access to basic needs. This would imply that higher inequality would result in higher acceptance of corrupt acts in the whole population. On the other hand, however, we might expect that in a European context, where levels of affluence and democracy are higher, and welfare states at least aim to achieve some level of basic security and equal opportunity, people in lower social positions might become increasingly less acceptant of corrupt acts. If we add also a self-interest argument (the lack of financial resources and power puts the members of lower social strata at a disadvantage on a playing-field where this is the currency), a stronger expectation is that among the lower social strata, higher income inequality translates into lower acceptance of corrupt acts (H2). As such, these contrasting arguments could tilt the balance either way and could explain the inconsistent pattern of relationships between income inequality and acceptance of corrupt acts as found in the literature so far.
Our data source is the longitudinal integrated file of the EVS. In our analyses, we included only the countries that had at least 2 waves of data collection. Some countries and waves were discarded because of missing values for the contextual income inequality2 and wealth measures3. Finally, we had 40 countries and 125 country-wave combinations in our analyses, covering the period from 1990 to 2017.
We followed Pop (2012) in measuring acceptance of corrupt acts. For the items ‘accepting a bribe’, ‘claiming undeserved state benefits’, ‘cheating on tax’ and ‘paying cash to avoid tax’, respondents that chose a score from 6 to 10 (on a scale from 1 to 10, where a higher value indicates more acceptance) were coded with 1. Around 22 percent out of 181504 respondents in the working file found justifiable at least one of these corrupt acts. However, we found large differences between countries within each wave in the proportion of the population that found any of the 4 acts acceptable. The Russian Federation stands out with almost 60 percent of the population that found corrupt acts acceptable in the 2017 wave, while on the other end we had Turkey where in 1999 wave only around 3 percent of the population found corrupt acts justifiable.
We first explored within each wave the country-level bivariate relationship between the level of income inequality or wealth and the societal acceptance of corrupt acts. Figure 22.1 presents an unclear picture:4 the relationship is not significant in the 1990-wave, is negative in 1999, remains negative but weakens in 2008 and finally became positive in the 2017-wave. The correlations within each wave indicated that all these relationships were however not statistically significant.
The bivariate relationship between the proportion of respondents that found any of the four corrupt acts justifiable and the level of economic affluence within each wave showed a more consistent negative pattern (Figure 22.2). However, these relationships were also not significant.
To test our expectations formally we applied the method proposed by Fairbrother (2014). In brief, we estimated a 3-level multilevel model with country-waves nested in countries. Although the acceptance of corrupt acts was a dichotomous measure, we followed Mood (2010) and estimated linear probability models, treating thus the dependent variable as continuous and expressing the probability to find corrupt acts justifiable. To capture the effect of the level and of the change in time in income inequality we computed two measures, one capturing the mean by country across the waves in the dataset and the other one as the difference of each wave to the grand mean within the country. We added a set of individual-level control variables (gender, labour market position, age, and education level in 3 categories) as well as dummies for the waves. We used the same strategy to decompose the GDP per capita measure into the mean and difference to the country-specific mean. We used the harmonized level of education provided in the integrated datafile as a proxy for the socio-economic position of respondents. This resulted in discarding the 1990 wave due to missing values. This solution was preferable to using a measure of income at the individual level that additionally suffered from high levels of missing values when collected.
Did the increase of income inequality between 1999 to 2017 relate to higher or lower probabilities of finding corrupt acts justifiable? Based on our analyses, this was not the case.5 Similarly, the average of income inequality across the waves included in the analyses was also not linked to the probability of finding corrupt acts justifiable. The same can be said about the two (between- and within-) measures of wealth. Moreover, the estimation of interactions between over-time changes in income inequality and education level dummies, led to the same conclusion, i.e., there was no significant or significantly different impact of trends in income inequality on the attitudes towards corrupt acts for individuals with different education levels.
We then turned our attention to possible ‘cluster-effects’, whereby ‘families of countries’ with similar religiously-rooted institutional and legal-historical traditions and regulations, which also happen to cluster around certain levels of inequality and economic affluence, systematically vary in terms of value orientations. Based on the sources of variations mentioned above (also see e.g. De Jong, Lalenis & Mamadouh, 2002), we assigned countries to a ‘preliminary’ and admittedly rough classification differentiating between a Northern-European (Protestant, Common Law or pragmatic/decentralized law system, Beveridgean welfare state origins), a Southern-European (predominantly Catholic, French or Germanic Civil Law, conservative-corporatist social and labour market policy) and an Eastern-European cluster (legacy of communist rule, Catholic/ Orthodox). We found that, when not including the level of inequality and of wealth, the level of acceptance of corrupt acts was significantly higher in the Southern and Eastern clusters. Including the level of and the changes in time in wealth and inequality did not explain away these effects. Including interactions between the level of and changes in income inequality, and the cluster dummies resulted in a significant interaction with the Eastern-European cluster: in those countries with higher levels of inequality, the overall higher acceptance of corrupt acts was significantly lower.
Attitudes towards corrupt acts display a wide variation between countries – from around three percent of the population in Turkey 1999 that found any of the four corrupt acts justifiable to almost 60 percent in the Russian Federation in 2017. Also, as illustrated by the figures, a change in time and within countries in the acceptance of corrupt acts is visible. Still, and against arguments and previous evidence from the literature, we found no relationship between the ‘average’ level or the changes in income inequality and the acceptance of corrupt acts. This comes as a surprise because it contradicts a study that using data from the EVS 2008 wave found an overall negative association between income inequality and the acceptance of corrupt acts (Pop, 2012). In addition, it also contradicts the study by You & Khagram (2005), who expected and found an ‘overall’ positive effect of income inequality on perceived corruption; this effect was mediated by a higher acceptance of corruption.
How can we explain these inconsistent findings? We proposed a more theoretical reasoning and we argued that high levels of income inequality might be perceived differently by individuals with different social standing. However, this was not the case also. Possibly, other contextual factors play a role in modelling how income inequality is perceived within the population and subsequently, what kind of effects it might have. First, Mijs (2019) finds that increasing income inequality across European countries is associated with a higher tolerance of inequality as more people believe that higher income gaps are meritocratically deserved. If this is the case, then “deserved” inequality is likely not reflected in attitudes towards corruption through the arguments that we discussed.
Next, engagement in corrupt acts as a cultural facet of Eastern-European societies could also have a role in moderating the effect of income inequality on the acceptance of corrupt acts, especially in combination with the profound institutional and economic changes that also have led to often strong increases in income inequality after the fall of communism. Corrupt acts could have a dual role in these societies, on the one hand being embedded still in the social psyche, being condemned as a social problem but still safeguarding the access to public resources in a context of acute instability. This possibility was also supported by the analyses where we examined the differences between clusters of countries, in particular the finding that the overall higher acceptance of corrupt acts in Eastern European societies was significantly lower in those countries with higher levels of inequality.
As a conclusion to this chapter, we point out the higher acceptance of corrupt acts in the Southern- and Eastern-European countries compared to the Northern countries. ‘Acceptance of corruption’ seems to be a rather ‘stable’ characteristic of countries associated with typical religiously-rooted social institutions and legal traditions. Future research could flesh out which macro-level institutional arrangements (e.g., religion) are associated with which micro-level social attitudes and norms related to the ‘acceptance of corruption’.
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