Can Elections Combat Corruption? Contextual Factors and Individual Biases

Transcription

1 Can Elections Combat Corruption? Contextual Factors and Individual Biases Georgios Xezonakis Quality of Government Institute Department of Political Science, University of Gothenburg Sprängkullsgatan 19 Göteborg SE Sweden Phone: Spyros Kosmidis Department of Politics & IR, University of Oxford, UK Phone: Stefan Dahlberg Quality of Government Institute Department of Political Science, University of Gothenburg, Sweden Phone: Abstract While the accountability through elections mechanism is often considered a force that can combat corruption, the individual propensities to engage in corruption voting have been neglected in the literature. In this paper we are concerned with what drives variation in corruption voting across countries with diverse institutional arrangements and across voters with heterogeneous individual attributes. We argue, and findings suggest that it is so, that features of the party system related to clarity of responsibility in terms of policy outputs and stable system features such as plurality electoral rules might prime corruption as an issue in voting calculations and therefore increase accountability. At the voter level, attributes do not seem to affect corruption voting in the desired direction. Longlasting attachments to political parties that serve in office tend to subvert the accountability mechanism. As a result, punishment for corruption is limited to opposition partisans and independents. We test our expectations with a combination of individual level survey data from Module 2 of the Comparative Study of Electoral Systems and macro level data on institutional arrangements.

2 Introduction Political accountability is a fundamental feature of and a yardstick for evaluating democracy (Powell, 2000). The effectiveness of democracy in keeping those in power in check is wholly relevant in the case of corruption. A large body of research has engaged into a review of the systemic/contextual factors that can account for variations in the levels of corruption at the aggregate level. A number of country specific factors have been deemed relevant in this sort of studies (see Persson et al., 2003; Kunicova and Ackerman, 2005, Charron, 2011, Chang and Golden, 2007). The argument here is that different institutional arrangements (e.g. constitutional arrangements or the electoral formula) provide differential incentives and opportunities to elites to engage in corrupt behaviour and extract rents. Similarly, it provides differential opportunities and incentives to both elites and voters to monitor, and for that matter sanction, corrupt behaviour (Charron, 2011). Here we are concerned, firstly, with the contextual conditions that are related to variations in corruption voting and we specify four contextual conditions that can enhance the individual voting weights placed on corruption. We take insights from the economic voting literature (Powell and Whitten, 1993) and from research on the determinants of corruption (Tavits, 2007; Kunicova and Ackerman, 2005; Chang and Golden, 2010; Chang, 2005; Charron, 2011). We argue that features of the party system related to clarity of responsibility in terms of policy outputs, the electoral rules and the size of the party system, influence the voting weights employed by individual voters when they cast their votes. We also argue that individual voter characteristics also play a role in corruption voting. We assume that the perceptions of corruption will loom larger to different voting groups and anticipate that cognitive resources (e.g. education) and 1

3 voter cues and shortcuts (such as party identification) will moderate the relationship between corruption perceptions and incumbent voting. The empirical results suggest that corruption perceptions are primed as an influence on the vote in plurality electoral systems, during elections with a long ran chief executive and in legislatures with a smaller number of parties. However the accountability mechanism does not seem to be driven by individual characteristics in the desired direction. If anything, long-term psychological attachments to parties diminish the effects of corruption perceptions on the vote. This paper makes two contributions. It is the first --to our knowledge-- that models individual voter propensities to reward or punish incumbent politicians for widespread corruption. Our second contribution relates to our findings. Our inferences, which are based on a comparative pool of voters from 23 democracies, show a) how institutional arrangements can enhance the quality of democratic interactions and b) reaffirm the importance of cognitive skills and biases (i.e. partisanship) in the way voters decide about their future. This has important implications for representative democracy. The empirical findings carry implications both for voting behaviour models and research on the mechanisms available in electoral democracies to reward or punish (un)corrupt political elites. In the remainder of this paper we first provide a theoretical justification of the contextual and individual level features that we expect should prime corruption voting. In the next section we present the data that we are using to test the hypotheses. Here we take advantage of Module 2 of the Comparative Study of Electoral Systems that includes questions about voting behaviour together with perceptions of how widespread corruption is. Results of the empirical models will follow and the paper will conclude with some final remarks. 2

4 Electoral Accountability for Corruption The main question we are concerned with in this paper is, what drives variation in corruption voting. Much like the case of economic voting we consider corruption voting as a product of the evaluation of the incumbent from the part of the voter (as regards corruption) and a corresponding choice come election day (punish or reward). 1 The premise on which this paper is based is related to an observation that is often cited to underline the apparent difficulty of liberal democracy to combat corruption through elections. Political accountability is a principal component of the democratic system and in the case of corruption the ability of voters to hold politicians accountable for misconduct (or their negligence to halt public sector corruption) is of crucial importance. Evidence suggests that, more often that not, this is not the case: Corruption charges do not necessarily hurt reelection prospects and even if legislators are somewhat punished at the polls vote losses are still quite modest (Chang et al., 2010, Costas-Perez et., al, 2012; Reed, 1999; Peters and Welch, 1980; Welch and Hibbing, 1997; Dimock and Jacobson, 1995; but see Ferraz and Finan, 2008). This finding holds in a diverse set of cases spanning countries like the US, the UK, Italy or Spain (Rundquist et al, 1977; Dimock and Jacobson, 1995; Eggers and Fisher, 2011; Reed, 1999; Chang et al., 2010; for a review, Muñoz et, al., 2012; Anduiza, et, al., 2014) Similar findings suggest that good economic performance and inherent system failures such as clientelism are likely to temper the effect that political corruption perceptions can exert on government support (Manzetti and Wilson, 2007; 1 In a recent manuscript Klasnja, Tucker and Deegan-Krause (2012), put forward a similar idea like the one presented here. They use a parallel with economic voting and the distinction between sociotropic and pocketbook voting, suggesting that personal experiences with corruption (pocketbook corruption voting) and perceptions of the prevalence of corruption (sociotropic corruption voting) are two distinct mechanisms through which corruption voting works. In that sense this research is mostly concerned with what can account for variations across (and intra) country in sociotropic corruption voting. 3

5 Zechmeister and Zizumbo-Colunga, 2013). Research also suggests that punishment at the polls is conditional upon the information that voters receive regarding malfeasance or government performance in general (Chang et al., 2010; Costas-Perez et., al, 2012). The media obviously play an important role in this process. When corruption is primed as an issue through increased coverage and therefore politicized, it can displace other issues from the political agenda and enhance what one could call corruption accountability (Chang et., al, 2010). These studies highlight the importance the visibility of corruption in the news has, and the quality of information on that issue (Costas-Perez et al., 2012). Our main concern here is not what drives perceptions of corruption (corruption perceptions as dependent variable) but rather what might prime these perceptions at the polls. This work is similar to research that identifies institutional and contextual variables that might lead to incumbent votes losses (Krause and Mendez, 2009), or those that identify the effect of systemic variables on levels of corruption (Charron, 2011; Tavits, 2007). As it is the case in accountability models that examine the role of economic performance, different voting groups place heterogeneous voting weights on the economy (see for example, Gomez and Wilson, 2006; Kosmidis and Xezonakis, 2010). Similarly, we seek to evaluate which individual level characteristics might moderate the importance of corruption evaluations in voter calculations. Institutional Structure and Clarity of Responsibility The problem of accountability in representative democracies has been efficiently described in various accountability models as an agency problem (see e.g. Besley, 2006; Groenendijk, 1997; cf., Persson, Rothstein and Teorell, 2013). Agents (politicians) are selected to deliver virtuous policies and oppose vicious practices 4

6 and principals (voters) are supposed to monitor this process and hold agents into account: re-electing them if they delivered and voting them out if they did not. In this process, we argue, the moderating factor of a robust accountability mechanism is the quality and clarity of the monitoring opportunities. The monitoring process itself is based on two different sets of factors that relate to the ambiguity or the clarity of information regarding corruption for any given voter at any given context. We argue that institutions are the main systemic factors that can obfuscate or assist the monitoring process. The argument here is that different institutional arrangements (e.g. constitutional arrangements or the electoral formula) provide differential incentives and opportunities to elites to engage in corrupt behaviour and extract rents. Similarly, it provides differential opportunities and incentives to both elites and voters to monitor, and for that matter sanction, corrupt behaviour. At the constitutional level, the number of veto points seems to be relevant. Presidential and federal systems with high institutional competition tend to constrain corruption and provide fewer opportunities for rent extraction (see Persson and Tabellini, 2003; cf. Kunicova and Ackerman, 2005). Another stream of research originates in a classic (albeit empirically refuted) formulation by Myerson (1993) and mainly focuses on the electoral system and its implications: Corruption should thrive in two party systems (SMD systems) and should become easier to combat as more (and new) parties contest elections (PR systems). Subsequent tests show that the data do not fit the theory. The short story and the prevailing finding is that, majoritarian systems provide more constrains on corruption as compared to Proportional Representation (PR) systems (Kunicova and Ackerman, 2005). Monitoring difficulties for both voters and political opponents are greater in PR systems as collective action problems for the aforementioned groups are more likely in those 5

7 settings (Kunicova and Ackerman, 2005: 597). More nuanced approaches fine tune this argument by focusing on additional institutional characteristics like district magnitude, electoral formula or ballot structure (Charron 2011; Chang, 2005; Chang and Golden, 2007). Ultimately, wherever the actual mechanism rests on (either the side of the voters or the side of the elites), the main assumption is that voters take their evaluations about corruption in the polling booth and vote accordingly. Increased accountability should, therefore, lead to a more compliant behaviour from the part of the agent (i.e. less corruption). However, as others point out the varying monitoring opportunities cannot rest solely on constitutional or electoral arrangements (Tavits, 2007: 219). Theoretical arguments based on such factors provide less robust theoretical predictions as to the direction that the relationship between constitutional arrangements/electoral system and corruption takes (Tavits, 2007). The argument here is that taking into account solely the formal institutional structure of the party system might obscure the full range of accountability enhancing features available to the voters and as such the opportunities for monitoring and control. Tavits (2007) applies an economic voting idea to corruption and argues that clarity of responsibility is the important feature of a party system that one should focus on when exploring how variation in monitoring opportunities is related to variations in corruption levels. The classic formulation of clarity of responsibility states that in understanding variation in the size of economic voting across countries one needs to pay attention to how blurred or clear the lines between government and opposition are regarding their influence on policy outputs and more specifically on economic policy: If the legislative rules, the political control of different institutions, 6

8 and the lack of cohesion of the government all encourage more influence for the political opposition, voters will be less likely to punish the government for poor performance of the economy. Responsibility for the performance will simply be less clear (Powell and Whitten, 1993:393). So it is the diffusion of responsibility along with political power that is important here. Previous research has demonstrated that the clarity of responsibility argument is relevant in the case of corruption. To the degree that corruption can be considered governmental output as much as reducing unemployment or inflation and increasing growth, then governments are expected to be punished by the principals when corruption prevails in a country and vice versa. Therefore political contexts that increase clarity of responsibility will exhibit less corruption (Tavits, 2007). The above represent two distinct approaches regarding the relation between political context and corruption. One focuses mostly on formal rules and institutions and the second incorporates features of the political system that are related (and to a degree causally) with the institutional structure but can exhibit more variation through time, inside contexts with similar institutional configuration. Following Powell and Whitten (1993) and Tavits (2007) we focus mainly on majority status of government, cabinet duration and the degree of party system fragmentation in order to test the clarity of responsibility argument. According to Powell (2000) the main indicator of clarity of responsibility is the degree in which one party has control of both the executive and legislative branches of the government. Minority governments (control only over the executive) represent the lower clarity setting since executives in this case cannot initiate and enact legislation without the support of other parliamentary parties. Various collation governments 7

9 (shared control of both the executive and legislature) fall somewhere in between in the clarity scale. We further argue that a short-lived government could not prime voter perceptions of political corruption, at least not to the extent that a government with a lengthy tenure in office would. Cabinet duration is, therefore, another obvious way through which voters can filter information and hold the system accountable for corruption. Note here that this prediction is not concerned with how government duration might be related to corruption levels. Quick succession of governments in power might provide more incentives for elites to engage in corrupt activities and, in the long run, increase the overall levels of corruption. But as far as voter information is concerned using corruption as a yardstick for their choice might not be easily achievable. The size and fragmentation of the party system is also relevant. While the ability to assign blame is important the accountability mechanism might not work if voters cannot identify an equally clear and potentially viable alternative. This can work on the opposite direction though. Monitoring of government corruption on the elite side is higher in multiparty systems and therefore information for voters plentiful and possibly more salient. It is therefore an open question as to whether party system fragmentation will prime or not corruption voting. To summarise at this point, we expect plurality electoral rules, majority and long lived governments to increase corruption voting while we are agnostic about the effects of the effective number of parties. 8

10 Individual level Attributes Contextual variation in corruption voting tells an important part of the story particularly the portion related to how systemic differences across countries condition the levels of corruption voting. On top of contextual variation we posit that different voters within nations may place different weights on considerations like corruption when they cast their vote. We are interested here in the role of education, political information and partisanship. The former two examine whether voters who are cognitively mobilised are more likely to place more voting weights on corruption. The latter addresses the potential that individual cognitive biases have to subvert the accountability process. Our argument posits that in a democracy with voters being fully informed and a democracy with voters bearing no information whatsoever, politicians will have more chances to extract rents. In the latter example corruption will be widespread and in the former the model equilibrium will predict no corruption at all (see Barro, 1973; Ferejohn, 1986; Persson and Tabellini, 2003). Given that both examples use the extreme --democratic-- cases, the variation in the levels of information within the electorate will determine the degree of accountability. In other words, political experts (as compared to novices) will place more weight on corruption when they vote for the incumbent. The second group of individual attributes corresponds to affective sources such as party identification (Campbell et al., 1960). Whereas cognitive skills can enhance information seeking and increase attention to the mass media, some voters hold biased views about the political environment and thus filter political information in response to their political predispositions. This suggests that incumbent partisans 9

11 will place less weight on corruption when they vote, while corruption will disproportionately drive the decisions of opposition partisans. The argument is intuitive and extends the argument made by Anderson and Tverdova in their research on how corruption shapes attitudes toward government (see Anderson and Tverdova, 2003). They base their argument on the notion that partisans tend to evaluate government performance more favourable in a number of political domains including economic performance and corruption (Bartels, 2002; Tilley and Hobolt, 2011). In line with that research, we also argue that political independents, but most predominantly, opposition partisans will place much more weight on corruption perceptions. Experimental evidence confirm that partisans are indeed are less likely to even perceive and acknowledge corruption per se, while political information tends to temper the effects of partisan bias (Anduiza et al., 2014). To summarize, we expect cognitive attributes and skills such as higher degree of education and political information to prime corruption evaluations in voting decisions while partisanship should temper that effect. Data Module 2 of the Comparative Study of Electoral Systems (CSES) is the core database used in this analysis. The CSES module 2 compiles 40 post election surveys in 38 countries. For the purposes of this paper we focus on parliamentary democracies. This and a combination of other data limitations, limits the sample of available election studies to 23 (see Appendix table A1 for a list of countries and election studies). The CSES provides the main level-1 variables used in the voting models: i) a dichotomous dependent variable that measures incumbent voting; and ii) the key independent variable of perceptions about corruption. The dependent 10

12 variable is scored as 1 if the party the respondent has voted for was in government during previous incumbency term and 0 otherwise. Non voters are excluded from the analysis. The survey question on which the main independent variable is based measures, on a 4 point scale, answers to the question How widespread do you think corruption such as bribe taking amongst politicians is in [country]: it hardly happens at all, not very widespread, quite widespread, very widespread? (for a review of these data see Holmberg, 2009). Admittedly for the purposes of this project the question is not ideal. First it might limit respondents to the scenario of political corruption. It concentrates it to the behaviour of politicians and other instances of corruption for example in the public sector, might not be captured. Therefore the performance of the government in combating corruption in general, might not feature much in the respondent s answer. We cannot really be sure whether the cue such as prevents respondents from considering other instances of corruption. It does represent, however, an evaluation of how efficient or inefficient politicians are in the exercise or their duties and, of course, on the quality of their policy-making. Another issue with this question is that it does not take into account individual experiences with corruption. Much like egocentric and sociotropic economic voting, corruption might be primed for voters only in cases where they have been personally and directly affected by corrupt activity (e.g. having to pay bribes to public officials). However, we do believe that this survey item captures important variation in voters perception about corruption. From the remaining individual level variables, education is based on the original variable in the CSES-modules consisting of eight categories. Party identification measures whether a respondent is more closely attached to a specific 11

13 party and scores 1 if this party is one of the incumbent parties and 0 otherwise. Political information is constructed as an additive index, stretching from 0 to 3, based on the three information items included in the CSES. For some of the systemic variables we rely on the Database of Political Institutions (DPI) compiled by Beck, Keefer and Clarke, (2001, updated through 2010), along with publications from the Inter-Parliamentary Union. A combination of the seats in parliament for the government and the number of parties in government gives the measure of majority status. This is scored as 30 for minority governments, 60 for coalition governments, and 100 for one party majority government (as in Powell, 2000). Time in government for the chief executive gives the indicator for the cabinet duration. The rule of thumb has been that when a new party enters a government coalition, even if the prime minister stays the same, the cabinet duration variable starts again from zero (note that alternative classifications sensitive to these issues leave results unchanged). For the party system fragmentation variable we relied on publications by Gallagher and Mitchell (2008) on the effective number of electoral parties based on vote-shares. We use the electoral rule that governs the allocation of the majority of house seats (proportional, mixed and plurality) to classify countries according to electoral system. The classification is made by Holmberg (2011). For a descriptive overview of the system related variables, see appendix A. Results All models report results from multilevel logistic regressions with random intercepts. Estimating a pooled data model in the 25 election studies in our sample can lead to erroneous conclusions if there are unobserved differences between countries (Hsiao 2003; Greene 2007). Thus we estimate a random intercept model that takes into account country-specific effects to ensure that unobserved differences 12

14 between countries are not driving key findings. This approach does deal with some of these potential problems with clustered data (see Arceneaux and Nickerson 2009). The following equation presents the basic model specification: Incumbent Vote= - B 1 Corruption+(controls) +B 2 Corruption*Attributes +B 3 Context -B 4 Corruption*Context (level 1) (level 2) (cross-level) Perceptions about how wide spread corruption are interacted with the four features of the political context described above. To be sure, we expect perceptions of corruption to exert a negative effect on incumbent voting. Level-1 control variables include evaluations of government performance (higher values in this variable indicate a very bad job ) and ideological distance between voters' self-placement and the ideological position of the government on the left right scale (in the case of coalition governments the mean placement of all coalition partners is considered the government s position on the left right). Table 1 reports results of five different models. In the first model the interaction is between perceptions of corruption and majority status of government, in the second model the interaction term is with cabinet duration, the third model with party system fragmentation and the fourth with the electoral system. All models control for the overall levels of corruption in the country using Transparency International s Corruption Perception Index. One reason for including a global measure of corruption is that individual perceptions of corruption seem to interact with corruption on a more general level (Dahlberg and Solevid, 2013). We are also controlling for economic performance in terms of growth in GDP per capita through all models since we know that economic performance usually have a positive impact on the likelihood of supporting incumbent governments. 13

15 (Table 1 about here) Three out of the four interaction terms appear to be significant. Corruption evaluations have an added effect on voting the more years a government is in power and less of an effect as the party system becomes more fragmented. For the third model the negative sign suggests that we can expect more corruption voting in plurality electoral systems. 2 Since we have interaction terms and logit coefficients we also visualise our findings to facilitate the interpretation. Figures 1 to 4 plot the marginal effect of corruption perceptions for the four interaction terms. Marginal effects below the zero value on the Y-Axis denote corruption voting. More negative values signify higher levels of corruption voting. Figure 1 visualises the Marginal Effect of corruption perceptions for different values of our Majority Status variable, with 95% confidence intervals. The plot reveals a largely negligible interaction effect as confidence intervals seem to overlap. In Figure 2 we plot corruption voting conditional upon our Cabinet Duration variable. The graphing of the effect suggests that anything less than five years in government is not enough for corruption perceptions to have a significant impact on voting for an incumbent but as tenure increases corruption seems to become more salient in voting decisions. Similarly, in a system that has upwards of 5 effective parties corruption perceptions do not seem to exert a significant effect on voting behaviour as is evident in Figure 3. (Figure 1-4 about here) 2 Note that these models have been tested using alternative specifications and controls. For example in the case of model 3, a control for the electoral system (that can account for party system fragmentation) does not alter the results. Also a full model containing the full range of systemic variables and interaction terms leaves substantive results unaffected. 14

16 Finally, regarding the interaction in Figure 4, we find that a major difference is to be found between systems with proportional versus plurality electoral formulas. The classification of electoral systems is not always as straightforward as one can expect and in this respect we also specified a model where we have contrasted clearly plurality systems against everything else, with substantive results unchanged. Figure 4 suggests that corruption voting is borderline significant in PR systems but clearly much larger in systems where the the legislature is chosen by plurality rules. All in all, the clarity of responsibility argument seems to hold for the two out of the three features that were specified (cabinet duration and effective number of parties). As was expected plurality systems tend to provide more opportunities for corruption voting as opposed to PR systems. Table 2 shows the interaction effects between corruption perceptions and different individual characteristics relating to cognitive and affective resources, such as education, political information and party identification. Just as in Table 1, perceptions of government performance and ideological distance together with the Transparency International 's corruption perception index and GDP growth per capita are included as controls through all models. (Table 2 about here) Apparently only one out of three interaction terms yields a significant impact on corruption voting. Voters who identify with the incumbent party(ies) seem to be more forgiving when it comes to corrupt behavior in general. The likelihood of punishing incumbent parties is thus in general higher among voters who perceive the political 15

17 corruption to be widespread but this behavior is less common among those who identify with any of the incumbent parties. We also hypothesised that higher levels of education would predict more corruption voting but this expectation is not supported in our data. It should be mentioned that we have elaborated with different coding of education (such as low versus high education; low, medium, high education etc.) but the results stay the same. Figure 5 confirms the findings from Table 2. The non results are very clear as regards education. Regarding political sophistication, here operationalized in terms of political information based on three information items included in the CSES data, figure 6 reveals differences between the least informed voters versus the rest (confidence intervals in the low information group are the only ones which overlap with zero suggesting no significant effect of corruption perceptions in that group). There are, however, no statistically significant differences between the other three groups of voters holding some kind of political information. This suggests that there might be something to the story here but results seem not to be very robust in this case. (Figure 5 to 7 about here) Finally, Figure 7 suggests that incumbent partisans are not only unable to punish corrupt behaviour but more likely to look the other way, if not reward it. Opposition partisans and independents clearly punish, but with lesser intent. We consider this to be an important finding with severe implications for democratic politics. 16

18 Conclusion In this paper, we have examined some of the contextual conditions and individual level attributes that can account for variations in corruption voting. We have argued that different features of the political and institutional context can lead to varying degrees of corruption politicisation and therefore prime corruption voting in different ways. Taking insights from the economic voting literature (Powell and Whitten, 1993) and from research on the determinants of corruption (Tavits, 2005; Kunicova and Ackerman, 2005; Chang and Golden, 2010; Charron, 2010), we argued that features of the party system related to clarity of responsibility in terms of policy outputs, the electoral system and relative levels of corruption might increase corruption voting. Results have indicated that voters might allow for corruption input in their voting calculations when responsibility for policy outputs is clear (e.g. cabinet duration, compact party system) and when institutional rules favour a clear competition between two main parties (i.e. plurality effect). This result suggests that the electoral context does mediate the effect of corruption providing less or more opportunities for holding corrupt politicians to account. Educational attainment and political information do not seem to increase the chances towards an accountability geared vote unlike expectations both from corruption and economic voting research. We have clearer findings when we analyse party identification. Individuals who view politics through partisanship lenses are more likely to temper their predisposition to cast a corruption vote. What appears to be good for parties, and by implication electoral democracy, is bad for Quality of Government. It would be interesting to evaluate what is the moderating effect of party identification in high clarity contexts and future research in the subject should address this. 17

19 We have noted before a number of caveats for this research. More importantly, what the corruption question included in the CSES really measures. The fact that a) forms of corruption other than grand political corruption might not be captured and b) personal experiences with corruption are not measured at all might constitute a problem for this research. If anything, we believe that this underestimates the magnitude of the effects that were uncovered here and not really likely to annul them. In any case, the significance of corruption at the scale measured by this question is wholly relevant to voting behaviour and political accountability. Finally, an added caveat has to do with a possible omitted contextual variable, that of the possibility that a clear anti-corruption party is standing for election. This would certainly increase the politicisation of corruption with subsequent effects on voting behaviour (Klasnja, Tucker and Deegan-Krause, 2012, Bågenholm, 2012). 18

20 Appendix A Table A1. Countries, Election Studies and System Level Variables. Country Year Majority Status Cabinet Duration Eff. No. Of Parties Electoral System Corruption Perception Index GDP Growth % Australia Bulgaria Canada Czech Republic Germany Denmark Spain Finland Great Britain Hungary Ireland Iceland Israel Italy Korea Netherlands Norway New Zealand Poland Portugal Portugal Romania Sweden Mean: Std. Dev Comment: A combination of the seats in parliament for the government and the number of parties in government gives the measure of majority status. This is scored as 30 for minority governments, 60 for coalition governments, and 100 for one party majority government (as in Powell, 2000). Time in government for the chief executive gives the indicator for the cabinet duration (in years). Party system fragmentation is based on publications by Gallagher and Mitchell (2008) on the effective number of electoral parties in terms of vote-shares. Electoral systems are classified as 1 for proportional, 2 for mixed and 3 for plurality systems, as made by Holmberg (2011). The Transparency International CPI Score relates to perceptions of the degree of corruption as seen by business people, risk analysts and the general public and ranges between 10 (highly clean) and 0 (highly corrupt). 19

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25 Tables and Figures Table 1. Corruption Voting and System Level Characteristics Individual level variables eq1 eq2 eq3 eq4 Government perfromance *** *** *** *** (0.027) (0.028) (0.028) (0.028) Ideological distance *** *** *** *** (0.009) (0.009) (0.009) (0.009) Corruption perception ** 0.174*** *** (0.066) (0.058) (0.087) (0.049) System level variables Corruption perception index (CPI) * 0.067* (0.039) (0.043) (0.039) (0.040) GDP per Capita Growth (%) 0.102* 0.094* Cross-level Interactions Majority status (0.053) (0.054) (0.053) (0.056) (0.004) Corruption*Majority status (0.001) Cabinet duration 0.085* (0.051) Corruption*Cabinet duration *** (0.010) Effectiv # of parties * (0.095) Corruption*Effectiv # of parties 0.041** (0.020) Electoral system 0.361** (0.144) Corruption*Electoral system *** (0.029) Constant 2.482*** 1.907*** 3.232*** 2.023*** (0.405) (0.368) (0.467) (0.363) Std. dev. Intercept, lev Rho N: Individuals N: Countries Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 24

26 Figure 1. Marginal Effect of Corruption Perceptions over Majority Status Figure 2. Marginal Effect of Corruption Perceptions over Cabinet Duration Figure 3. Marginal Effect of Corruption Perceptions over Effective Number of Parties Figure 4. Marginal Effect of Corruption Perceptions over Electoral System 25

27 Table 2. Corruption Voting and Individual Level Characteristics Individual level variables eq1 eq2 eq3 Government perfromance *** *** *** (0.028) (0.028) (0.034) Ideological distance *** *** *** (0.009) (0.009) (0.011) Corruption perception *** Education * (0.085) (0.045) (0.028) (0.075) Political information (0.059) Party Identification (incumbent) 2.945*** Corruption*Education (0.027) Corruption*Political information (0.021) (0.176) Corruption* Party identification 0.402*** System level variables (0.065) Corruption perception index (CPI) (0.039) (0.039) (0.039) GDP per Capita Growth (%) 0.104* 0.096* 0.138*** (0.054) (0.054) (0.053) Constant 2.951*** 2.540*** 1.147*** (0.388) (0.330) (0.317) Std. dev. Intercept, lev Rho N: Individuals 22,527 22,714 22,714 N: Countries Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 26

28 Figure 5. Marginal Effect of Corruption Perceptions over Education Figure 6. Marginal Effect of Corruption Perceptions over Political Information Figure 7. Marginal Effect of Corruption Perceptions over Party Identification 27