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Abstract

  1. Top of page
  2. Abstract
  3. Theoretical framework
  4. Data and methodology
  5. Findings
  6. Conclusion
  7. Acknowledgements
  8. References

West European right-wing extremist parties have received a great deal of attention over the past two decades due to their electoral success. What has received less coverage, however, is the fact that these parties have not enjoyed a consistent level of electoral support across Western Europe during this period. This article puts forward an explanation of the variation in the right-wing extremist party vote across Western Europe that incorporates a wider range of factors than have been considered previously. It begins by examining the impact of socio-demographic variables on the right-wing extremist party vote. Then, it turns its attention to a whole host of structural factors that may potentially affect the extreme right party vote, including institutional, party-system and conjunctural variables. The article concludes with an assessment of which variables have the most power in explaining the uneven electoral success of right-wing extremist parties across Western Europe. The findings go some way towards challenging the conventional wisdom as to how the advance of the parties of the extreme right may be halted.

West European right-wing extremist parties have received a great deal attention in the academic literature due to their electoral success. What has received less coverage, however, is the fact that these parties have not enjoyed a consistent level of electoral support in this third wave of right-wing extremist party activity; instead, their electoral fortunes have risen and fallen over the last two decades. That this variation – both over time and across countries – has attracted relatively little attention in the literature is not overly surprising. For one thing, there continues to be a shortage of comparative studies on the extreme right, particularly on its voters. In addition, many of the studies that do exist, not surprisingly have tended to focus only on why right-wing extremist parties have been successful, rather than on why they have not.

The few works that have addressed the issue of the variation in the electoral support for the parties of the extreme right across Western Europe have tended to offer only partial explanations for this phenomenon. Jackman and Volpert (1996), for example, assess the importance of electoral system, party system and economic factors on the right-wing extremist party vote, but they do not consider the impact of different socio-demographic variables. Likewise, Abedi (2002) concentrates on the effect of party system factors, but fails to examine the influence of socio-economic variables and other institutional characteristics. Knigge (1998), by contrast, explores the effect of some socio-economic factors, but does not examine the impact of electoral system or party system factors. Thus, while these studies each add to an overall explanation for the variation in the electoral fortunes of the parties of the extreme right, on their own, the account they offer is far from comprehensive.

The influential work by Kitschelt (1995) and the useful study by Lubbers and his colleagues (2002) provide more extensive explanations for the uneven electoral success of the parties of the extreme right. Yet, in spite of their more comprehensive nature and of the contributions they make to research on right-wing extremism, both studies suffer from a number of limitations. The framework employed by Kitschelt does not allow for a precise assessment of the relative influence of the different independent variables on the right-wing extremist party vote. The study by Lubbers et al. is problematic, too, in terms of its methodology, the countries it covers and its time-span. The decision to combine data from national election studies with data sets from supranational projects raises potential problems of validity and reliability, and the use of multilevel analysis is also open to question.1 As for the countries examined, the inclusion of those where support for the extreme right is extremely low is not without consequences. Finally, as regards the time-span covered, Lubbers and his colleagues analyze data from 1994 to 1997 only, and hence do not examine the early to mid-1980s – a time in which many right-wing extremist parties of the third wave broke through into the electoral arena. This means that the variance in explanatory factors such as unemployment, immigration and the positions of other parties is rather restricted.

In light of the limitations of the existing studies, this article puts forward an explanation of the variation in the right-wing extremist party vote across Western Europe that incorporates a wider range of factors than have been previously considered and covers a longer time period. More specifically, through the construction of an individual-level model, the article first examines the impact of socio-demographic variables on the right-wing extremist party vote. Then, by augmenting the model with system-level information, it investigates the influence of a whole host of structural factors (which together make up the political opportunity structure) that may potentially affect the extreme right's performance at the polls. This two-stage approach enables us to assess the extent to which system-level features (relating to the political opportunity structure) account for variation in the extreme right's success over time and across countries after individual-level features have been controlled for, thereby minimizing the probability of composition effects. Moreover, this approach also allows us to establish whether individual-level characteristics still have an effect on right-wing extremist voting when the political opportunity structure is held constant. Thus, we can estimate the impact of the socio-political structure on the extreme right's success in Western Europe.

Theoretical framework

  1. Top of page
  2. Abstract
  3. Theoretical framework
  4. Data and methodology
  5. Findings
  6. Conclusion
  7. Acknowledgements
  8. References

Socio-demographic factors

It has been well documented that certain socio-demographic groups have shown themselves more likely to vote for the parties of the extreme right than others. In the first instance, a significant gender gap in the support for the extreme right has been reported, with male voters exhibiting a greater propensity to vote for right-wing extremist parties than their female counterparts (see, e.g., Betz 1994; Lubbers et al. 2002). Similarly, previous studies have shown that age has an effect, with both younger and older voters more likely to support the extreme right than other age groups. A number of theories help explain this U-shaped phenomenon. It has been well documented, for example, that the decline in the effects of social structure has not affected all generations equally, and that younger voters and pensioners are more likely to lack social ties. This weaker social integration is likely to be reflected in lower levels of electoral participation as well as in a greater likelihood of voting for parties of the extreme right. A further explanation for the greater propensity of both young and old voters to support the extreme right rests in these people's interests and their access to welfare. Since young and old voters depend disproportionately on welfare, these two age groups are more likely to view immigrants as competitors than are people of other age groups.

As regards formal education, it is often hypothesized that people with lower levels of education will exhibit a greater propensity to vote for parties of the extreme right than those with higher levels of education. In the first instance, there is an economic or an interest-based argument to support this presumption: voters with lower levels of education tend to be less skilled, and hence are more likely to fall victim to market forces. They tend to support parties of the extreme right because these parties pledge to defend their economic interests by limiting the rights of immigrants and asylum-seekers, who are perceived as direct competitors both in the workplace and in access to social services and housing. Another argument is value-based and rests on the premise that, through education, people are intensively exposed to liberal values, and hence the longer people spend in education, the more likely they are to embrace such values (Warwick 1998; Weakliem 2002). A similar argument holds that cognitive style effects explain the link between the propensity to vote for a party of the extreme right and the level of education (Weil 1985).

Finally, as regards class, a number of national studies have shown shopkeepers, artisans and small-business people to be particularly well represented among the electorates of right-wing extremist parties in several countries. An over-representation of working-class voters among those who support the parties of the extreme right – in some cases right from the start; in other instances growing over the years – is also well-documented by many studies at the national level. Finally, it has also been argued that people in non-manual jobs who enjoy a small degree of autonomy in their work may also develop authoritarian preferences quite similar to those ascribed to working-class voters (Kitschelt 1995: 9).

Based on the evidence that has emerged in much of the existing literature, we therefore expect there to be a greater propensity to vote for parties of the extreme right among men, among voters who are either young or old, among those with lower levels of formal education, and among the working class, the self-employed and those in routine non-manual forms of employment compared to all other socio-demographic categories of elector.

Political opportunity structures

To assess the influence of structural or environmental factors on the right-wing extremist vote, we draw on the concept of ‘political opportunity structures’, which was originally developed in the context of research on social movements to denote the degree of ‘openness’ or ‘accessibility’ of a given political system for would-be political entrepreneurs. In a very influential study, Kitschelt (1986: 58) describes political opportunity structures as ‘specific configurations of resources, institutional arrangements and historical precedents for social mobilization, which facilitate the development of protest movements in some instances and constrain them in others’. As their name implies, political opportunity structures therefore emphasize the exogenous conditions for party success and, in so doing, contrast with actor-centred theories of success (Tarrow 1998: 18).

The concept of political opportunity structures is a broad one and different authors have included different items in their definition of the term. In spite of the differences, however, the majority of studies agree that fixed or permanent institutional features combine with more short-term, volatile or conjectural factors to produce an overall particular opportunity structure. We therefore propose to adopt a three-pronged approach with which to examine the influence of political opportunity structures on the right-wing extremist party vote: a first set of variables captures the impact of long-term institutional features on the parties of the extreme right; a second set examines medium-term factors that relate to the party system; and a third set of variables examines short-term contextual or conjectural variables.

Long-term institutional variables. Two institutional variables we regard as being of potential importance to how well parties of the extreme right perform at the polls are the electoral system and the degree of decentralization/federalism. As far as electoral systems are concerned, it has long been established that the more proportional the electoral system, the greater the incentives for political entrepreneurs to enter the electoral race and for voters to decide to support a new or small political party. By contrast, the less proportional the electoral system, the more leaders of new or small parties will be dissuaded from fielding candidates and the more discouraged voters will be from voting for such parties since they stand little change of gaining representation (Duverger 1951; Blais & Carty 1991). In view of this relationship, we anticipate that unless they have already reached a certain size and have a chance of continuing to attract a sizable section of the electorate, right-wing extremist parties are likely to record low electoral scores under disproportional electoral systems.

The effect of decentralization or federalism is less clear-cut. On the one hand, a high degree of decentralization (including regional parliaments) may foster the development of right-wing extremist parties because voters are more willing to support new and/or radical parties in ‘second order’ elections (Reif & Schmitt 1980). On the other hand, decentralization or federalism may be detrimental to right-wing extremist party success at the national (i.e., federal) level because rather than allowing extremist parties to gain a toehold in the electoral arena, second order elections may serve as a kind of security valve for the political system by providing citizens with an opportunity to express their political frustration with the mainstream parties without overly disturbing the political process on the national level. Therefore, two contrasting – yet equally convincing – hypotheses as to the effect of territorial decentralization exist.

Medium-term party system variables. Party system variables are less constant than institutional factors. For reasons of parsimony, we restrict ourselves to examining the impact of three such variables: the ideological position of other competitors in the party system, the degree of convergence between the mainstream parties and the coalition format in the respective party systems.2 We expect the position of the major party of the mainstream right in each of the party systems to have an impact on the success of the party of the extreme right, yet it is difficult to predict the exact nature of this impact. On the one hand, it can be argued that parties of the extreme right will perform poorly at the polls where the major party of the mainstream right is more right wing since in such situations there will be less political space available to the party of the extreme right. On the other hand, a more right wing mainstream right party may boost the electoral scores of the party of the extreme right by legitimizing the issues around which the extreme right mobilizes. Thus, two competing hypotheses emerge as to the influence of the ideological position of the mainstream right on the electoral success of the extreme right.

Next, we examine the degree of convergence between the parties of the mainstream right and the parties of the mainstream left in each of the party systems under observation.3 Here too, we explore two contrasting hypotheses. On the one hand, we can argue that right-wing extremist parties will benefit where the mainstream parties converge (Kitschelt 1995: 17). In such instances, the parties of the extreme right can credibly argue that if voters wish to see a real alternative to both the government and the mainstream opposition, then they should support the right-wing extremist party. When the mainstream parties are ideologically distinct from each other, it is more difficult for the parties of the extreme right to adopt this strategy. On the other hand, the extreme right might perform well at the polls when the mainstream parties are ideologically quite distinct. This distinctiveness may signal the lack of elite consensus (Zaller 1992), which might further extreme right party success. Alternatively, the mainstream parties may have diverged ideologically in an attempt to curb the advance of the parties of the extreme right in upcoming elections. Either way, ideological divergence between the mainstream parties may be associated with extreme right party success. Once again, therefore, two conflicting hypotheses exist as to the effect of ideological convergence of the mainstream parties on the right-wing extremist party vote.

We then move to consider the coalition format of the party systems under investigation. We predict that the extreme right will benefit from grand coalitions because voters will feel that there is a lack of other political alternatives during a grand coalition and because supporters of the mainstream right may become alienated if they do not see their preferred policies being enacted and do not enjoy the consolation of seeing their party play the role of a principled opposition (Kitschelt 1995: 17). Therefore, we anticipate that the right-wing extremist party vote will be higher in (or shortly after) periods of grand coalition government than it will be in periods of alternating government.

Short-term contextual variables. In addition to being affected by long-term institutional variables and medium-term party system variables, it is also reasonable to expect the right-wing extremist vote to be influenced by a number of short-term contextual factors. More specifically, given the considerable emphasis parties of the extreme right place on the issue of immigration from non-EU countries and on the supposed competition between immigrants and the indigenous population, we anticipate that levels of immigration and unemployment (both straightforward levels and also change in these levels) will exert an effect on how well the parties of the extreme right perform at the polls. We expect the right-wing extremist vote to be higher in situations where both the level of immigration and the level of unemployment are high.

Data and methodology

  1. Top of page
  2. Abstract
  3. Theoretical framework
  4. Data and methodology
  5. Findings
  6. Conclusion
  7. Acknowledgements
  8. References

The data in our analysis come from national election studies. The pooling and harmonizing was carried out under the auspices of the Extreme Right Electorates and Party Success (EREPS) Research Group.4 The major advantage of using national election studies is that they reflect voter behaviour at election time. This contrasts with supranational surveys (such as the Eurobarometer surveys, the World Values Surveys and those of the International Social Survey Programme), which may be carried out at a time close to the beginning of the electoral cycle in one country, but near the end of the cycle in another.

These national election studies provided us with information on the individual vote choices and the socio-demographic characteristics of West European electors. In contrast to some existing studies of right-wing extremist electorates (e.g., Van der Brug et al. 2000; Lubbers et al. 2002; Van der Brug and Fennema 2003), we do not include variables that capture the different attitudes of voters because there are very substantial problems in finding comparative indicators of attitudes in national election studies, both over time and across countries. Even the Comparative Study of Electoral Systems (CSES) data set (which is made up of national election studies) does not provide adequate data on attitudes that are of concern to us. While it does contain data on left-right attitudes, information on attitudes regarding immigration or minorities, for example, which is particularly relevant to a study of the extreme right, is absent. The country-coverage and the time-span of this data set also make it unsuitable for our purposes.5

Although there is clearly some trade-off to be had in deciding not to include attitudinal variables, we believe that the advantages of using national elections studies (rather than supranational surveys) outweigh any disadvantages that result from excluding attitudinal variables. Furthermore, in contrast to attitudinal data, socio-demographic data are relatively easily compared and are measured with much less error.

The countries included in our analysis are: Austria, Belgium,6 Denmark, France, Germany, Italy and Norway.7 This means that the parties included in our analysis are: the Freiheitliche Partei Österreichs (FPÖ), the Vlaams Blok (VB); the Fremskridtspartiet (FRPd) and the Dansk Folkeparti (DF); the Front National (FN); the Deutsche Volksunion (DVU), the Nationaldemokratische Partei Deutschlands (NPD) and the Republikaner (REP); the Movimento Sociale Italiano/Alleanza Nazionale (MSI/AN) until 1995;8 and the Fremskrittspartiet (FRPn).

In contrast to the study by Lubbers et al., we have excluded countries where support for the extreme right is extremely low. While we recognize that including countries in which there is no effective extreme right is certainly necessary in a macro-level explanation of the extreme right's success (and failure to do so would result in selection bias), we believe that incorporating such countries in an analysis of individual voting decisions is problematic for three reasons. First, voting for the reasonably established extreme right parties in countries like Belgium, France or even Germany is not comparable to voting for a tiny (and often fanatical) political sect. Second, not only are extreme right voters extremely rare in countries like Portugal, Spain, Great Britain and Ireland, but the number of respondents who report having voted for the extreme right in social surveys is even lower than the electoral results suggest (see Lubbers et al. 2002: 357). Third, in countries where the extreme right is very weak, prospective extreme right voters are often prevented from supporting an extreme right party because candidates of these parties are only fielded in certain constituencies. This is not reflected in surveys as such voters are coded either as non-voters or supporters of another party. The inclusion of survey data from countries where support for the extreme right is extremely low therefore dilutes and distorts any analysis of individual voting decisions.

While the parties included in our analysis differ from each other in terms of their precise ideological profile, we nonetheless believe that they belong to the same party family, and that they can thus be treated as constituent members of a larger, single group. There has been much debate in the literature over the exact definition of ‘right-wing extremism’, and hence over which parties belong to the extreme right party family, but a consensus has nonetheless emerged that a separate extreme right party family does indeed exist. While it is perhaps more heterogeneous than other party families, its constituent parts are distinct from the parties of the mainstream right, and they also share a number of ideological features (in particular some combination of racism, xenophobia, nationalism, and a desire for a strong state and law and order) that allow them to be grouped together at the far right end of the left-right political spectrum (see Ignazi 1992; Hainsworth 1992; Betz 1994; Mudde 1996, among others for further details of this debate). Further evidence of the fact that the parties included in our study belong to a common extreme right party family can be found in the series of expert judgments studies that have been carried out since the beginning of the 1980s (Castles & Mair 1984; Laver & Hunt 1992; Huber & Inglehart 1995; Lubbers 2000). The parties included in our study have been consistently placed furthest to the right on the left-right spectrum in these surveys.

Our timeframe spans the years 1984 to 2001. Our start date is informed by the broad consensus in the literature on right-wing extremism that the 1980s saw the beginning of a third wave of right-wing extremist activity in Western Europe. The majority of scholars of right-wing extremism also agree that the Scandinavian Progress Parties only became part of the right-wing extremist party family in the mid-1980s when refugee and immigration policies became their primary concerns (Kitschelt 1995: 121; Goul Andersen & Bjørklund 2000: 203–204). We therefore began with the Danish election survey of 1984, and collected all available data for polities where the extreme right was a relevant player in national parliamentary elections.

The socio-demographic variables included in our model are the standard ones: gender, age (<25 years, 25–34 years, 35–44 years, 45–54 years, 55–64 years, >64 years), formal education (no/primary education, middle school education, secondary education, university education), and social class (measured by a simplified Goldthorpe classification: professionals/managers, routine non-manual, self-employed, manual).

For our examination of the influence of political opportunity structures on the right-wing extremist party vote, we augmented the socio-economic data derived from the national election studies with information on the political systems and the party systems of the countries under investigation. To assess the impact of institutional variables, we made use of data (derived from Carter 2002) that measured the disproportionality of the electoral systems according to the Gallagher index (Gallagher 1991), and we adopted Lijphart's index of federalism to reflect the degree of territorial decentralization (Lijphart 1999). This ranges from 1 to 5, with 1 indicating a unitary and centralized state and 5 referring to a federal and decentralized state.

To explore the influence of the position of other political competitors and to assess the impact of mainstream party convergence, we drew on the data of the Comparative Manifesto Project (CMP) (Budge et al. 2001). From the CMP data, we constructed a measure based on the parties' policies on the issues of multiculturalism, internationalism, the ‘national way of life’ and law and order. While reflecting many of the components that make up the overarching left-right dimension, these policy items are particularly important to the parties of the extreme right as it is primarily along these dimensions that they compete with their mainstream rivals.9 Like all measures that are based on CMP data, it reflects the balance between ‘left’ and ‘right’ statements of a party. Negative figures indicate a leaning to the left, and positive numbers indicate a leaning to the right.10

To examine the effect of a grand coalition in the period directly before a general election, we drew on data from the European Journal of Political Research Political Data Yearbooks and included an appropriate dummy variable in our model.

Finally, to evaluate the effect of conjunctural factors on the decision to vote for the extreme right, we drew on unemployment data at the aggregate level11 and on data reflecting the number of asylum seekers in the countries under observation.12 We included a measure of the yearly number of asylum-seekers per 1,000 inhabitants,13 and a measure of the yearly percentage of unemployed people in the total workforce. We also included change rates for both variables in our model because according to the classical ‘J-curve’ reasoning (see Davies 1974; Coenders & Scheepers 1998), people might respond to changes rather than to the actual level of both measures.

In terms of methodology, we estimate a logit model with contextual variables. Our model thus allows us to estimate the probability of a voter voting for a party of the extreme right conditional on his or her individual socio-demographic attributes, and the particular political opportunity structures present in his or her country at the time of the election. Since there is no strong theoretical argument as to why socio-demographic or system-level explanations for an extreme right vote should vary systematically over countries and across time,14 we assume that the true regression coefficients are constant across countries and across time after controlling for both individual and contextual variables. Therefore, we refrain from inserting dummies and interactions to capture cross-country differences in intercepts and slopes.

Findings

  1. Top of page
  2. Abstract
  3. Theoretical framework
  4. Data and methodology
  5. Findings
  6. Conclusion
  7. Acknowledgements
  8. References

Looking at Table 1, we can see that our findings are in line with much of the previous research in the field.15 The results show that being male substantially raises the odds of voting for the extreme right. Put differently, depending on the respondent's other attributes, being male increases the probability of an individual being an extreme right voter by more than 50 per cent. This coefficient suggests that there is a substantial gender gap in support for the extreme right in Western Europe even when we control for other socio-demographic variables such as age, education and social class.

Table 1.  Socio-demographic model
Independent variablesbeb
  1. Notes: Robust standard errors adjusted for clustering on country are shown in parentheses (see Note 15); * significant at 5 per cent; ** significant at 1 per cent.

Male0.476** (0.036)1.609** (0.059)
Age <250.280* (0.124)1.324* (0.165)
Age 25–34−0.012 (0.114)0.988 (0.113)
Age 35–44−0.174 (0.095)0.841 (0.080)
Age 45–54−0.223** (0.074)0.800** (0.059)
Age 55–64−0.186 (0.112)0.830 (0.093)
No/primary education0.388 (0.304)1.474 (0.448)
Middle school education0.832** (0.244)2.299** (0.560)
Secondary school education0.624** (0.147)1.866** (0.273)
Professional/manager−0.054 (0.338)0.948 (0.320)
Routine non-manual0.116 (0.264)1.123 (0.296)
Self-employed0.243 (0.252)1.275 (0.321)
Manual0.345 (0.186)1.412 (0.262)
Constant−3.239** (0.235) 
N50,276 
Adjusted Pseudo-R2 (McFadden)0.03 
BIC−515,293 

Turning to the influence of age, Table 1 illustrates the U-shaped effect of this variable that we expected to see. Wald tests show that there are no significant (p = 0.45) differences in the respective levels of extreme right support among those voters who are between the ages of 35 and 64, while the level of support for parties of the extreme right among both younger and older voters is higher.16 The propensity to vote for a party of the extreme right among voters who are aged between 25 and 34 is identical (p = 0.91) to that of the reference group (voters who are 65 or older), while voters under the age of 25 are much more likely to vote for the extreme right than any other voters, including the reference group.

As regards levels of formal education, we predicted that people with lower levels of education would exhibit a greater propensity to vote for parties of the extreme right than people with higher levels of education. When we examine our model, however, things are not as clear-cut. While the low level of support that extreme right parties receive from university-educated voters (the reference group) is in line with the our predications, the coefficient for the group of voters with no education or with primary education is smaller than expected and is not significantly different from zero. We find, instead, that it is people with middle school diplomas who appear to form the core social base of the extreme right. Depending on his or her other characteristics, having a middle school education more than doubles the probability of an individual voting for the extreme right. The effect of being educated to secondary level is somewhat weaker, but the difference between the two coefficients is not significant (p = 0.19).

As concerns the effect of class, our findings are generally in line with our expectations. The results show that professionals and unclassified voters (the reference group) exhibit the lowest propensity to support extreme right-wing parties while the odds of an extreme right vote are somewhat higher if the respondent has a routine non-manual job, if he or she is self-employed, or if he or she is a manual worker.17

In a bid to summarize our socio-demographic findings, we calculated the expected probability of an extreme right vote across varying levels of the independent variables (see Table 2). For the sake of brevity, we restricted class to unclassified voters (the reference group) in the upper section of the table, and to workers (the group with the highest propensity to vote for a party of the extreme right) in the lower section of the table. Above all, Table 2 shows the significant variation in support for the extreme right that exists across the different socio-demographic groups. If, for example, we compare the predicted probability of a vote for the extreme right being cast by a female voter, aged 24 or less, with a university education and whose class is ‘unclassifiable’ with the predicted probability of an extreme right vote being cast by a male voter from the same age group, with a middle school education and a manual job, we can see the full extent of this variation. Indeed, Table 2 illustrate that the predicated probability of the female voter just described voting for a party of the extreme right is roughly 5 per cent (as shown in bold in the upper section of the table), whereas the predicted probability of the male voter just described voting for the extreme right is roughly 21 per cent (as shown in bold in the lower section of the table). This example clearly illustrates that gender and education in particular have a sizeable impact on the probability of voting for a party of the extreme right, while age and class are somewhat weaker predictors.

Table 2.  Predicted probabilities of an extreme right vote depending on gender, age, education and social class (percentage)
 FemaleMale
No/primary educationMiddle schoolSecondary schoolUniversity educationNo/primary educationMiddle schoolSecondary schoolUniversity education
  1. Notes: Typical 95 per cent confidence intervals based on robust standard errors adjusted for clustering on country: female, <25 years old, university educated, class ‘unclassified’: 2.9–8.2; male, <25 years old, middle school education, manual worker: 13.2–32.6.

Class: unclassified
Age <25711951116138
Age 25–345874813106
Age 35–44576371195
Age 45–54476371095
Age 55–64576371195
Age >645874913116
Class: manual
Age <25101412715211811
Age 25–34711951117148
Age 35–44610841015127
Age 45–5469841014127
Age 55–64610841015127
Age >64811951217148

So far our discussion has illustrated that a voter's socio-demographic attributes go a long way in helping to explain his or her propensity to vote for a party of the extreme right at election time. In addition to this, our results have by and large been in line with those of many of the existing studies on right-wing extremism. In particular, our comparative study of 24 elections in seven countries confirms that parties of the extreme right are strongest among the more marginalized sections of society, and that (even when we control for other socio-demographic variables) their support is predominantly male.

This agreement with existing studies notwithstanding, our results point to another important finding: the low adjusted (McFadden) pseudo R2 in our model (a mere 0.03) indicates that the variation in the electoral success of right-wing extremist parties both over time and across space cannot simply be explained by the different composition of the respective electorates. Instead, the variation in the electoral fortunes of the parties of the extreme right must be explained by factors other than socio-demographic ones. To confirm this we added a series of dummies for the 24 elections under study in our model (not shown) so as to create a model that captured all variation in the extreme right vote that could potentially be due to system-level factors. The resulting R2 of 0.09 was substantially higher than the R2 of the model in Table 1, thereby indicating that the extreme right's electoral success varies considerably over time and across space even if we control for the composition of the electorate. In light of this, we now augment our socio-demographic model shown in Table 1 with variables that relate to the political opportunity structure as discussed above.

Table 3 shows the results of the full model. Looking at the table, the first observation to make is that the coefficients for the socio-demographic variables have not greatly changed since we have augmented the model with the political opportunity structure variables.18 Second, we see that some of the additional variables have statistically significant and sizeable effects on an individual's propensity to vote for a party of the extreme right. Finally, we see a significant improvement in the model-fit: the pseudo R2 more than doubles and, more importantly, the BIC is reduced by 1106, meaning that the full model is clearly superior to the socio-demographic one.19 Given the nature of our explanatory variables, it is also worth noting that multicollinearity is not an issue in our model (see Arzheimer & Carter 2003: 31).

Table 3.  Complete model
Independent variablesbeb
  1. Notes: Robust standard errors adjusted for clustering on country are shown in parentheses (see Note 15); * significant at 5 per cent;** significant at 1 per cent.

Male0.471** (0.042)1.602** (0.068)
Age <250.364** (0.084)1.439** (0.120)
Age 25–340.084 (0.068)1.087 (0.074)
Age 35–44−0.096 (0.085)0.909 (0.077)
Age 45–54−0.200* (0.093)0.819* (0.076)
Age 55–64−0.148 (0.115)0.863 (0.099)
No/primary education0.571** (0.169)1.770** (0.300)
Middle school education0.753** (0.101)2.123** (0.215)
Secondary school education0.600** (0.128)1.822** (0.234)
Professional/manager0.007 (0.267)1.007 (0.269)
Routine non-manual0.082 (0.207)1.085 (0.225)
Self-employed0.265 (0.205)1.304 (0.268)
Manual0.361 (0.201)1.435 (0.288)
Disproportionality0.073** (0.017)1.076** (0.018)
Index of Decentralisation−0.116 (0.132)0.890 (0.117)
Ideological position of major party of mainstream right0.087 (0.045)1.091 (0.049)
Distance between major parties of mainstream left/right0.058 (0.033)1.060 (0.035)
Grand coalition0.699* (0.356)2.011* (0.715)
Asylum seekers per 1,000 inhabitants0.114 (0.077)1.121 (0.087)
Asylum seekers: Change−0.000 (0.000)1.000 (0.000)
Unemployment rate (%)−0.222** (0.045)0.801** (0.036)
Unemployment rate: Change0.006 (0.005)1.006 (0.005)
Constant−2.439** (0.148) 
N50,276 
Pseudo-R2 (McFadden)0.07 
BIC−516,399 

Starting with the two long-term institutional variables, we can see that the coefficient for the disproportionality of the electoral system is in fact positive, rather than negative as was anticipated.20 That is, the odds of voting for the extreme right actually increase as the disproportionality of the electoral system increases. At first we considered that this unexpected result might be caused by the inclusion of the French case, where the unique double-ballot system (whose disproportionality scores are extremely high) has not prevented the rise of the extreme right (see Arzheimer & Carter 2003). We therefore temporarily excluded France from the analysis. However, the coefficient for the disproportionality score hardly changed. The absence of a negative relationship between the disproportionality of the electoral system and the right-wing extremist vote has been reported elsewhere (Carter 2002), and two potential explanations for it have been put forward. It may be that right-wing extremist party voters are simply not aware of the consequences of electoral systems. Alternatively, the psychological effects of electoral systems may be weaker for right-wing extremist party voters than for other sections of the electorate, as many right-wing extremist party voters vote in an expressive manner and are not as concerned with their votes being translated into seats as are other voters. This latter hypothesis has clearly yet to be investigated.

As concerns the degree of decentralization and federalism, the coefficient is negative. However, since the coefficient fails the significance test, we remain unable to determine whether territorial decentralization fosters the extreme right party vote or whether it hinders it. Our data simply do not provide conclusive evidence as to which of the two hypotheses advanced above holds true in practice.

Turning to the medium-term party system variables, we can see that the position of the major party of mainstream right has a positive and borderline-significant (p = 0.05) effect on the right-wing extremist party vote. A move to the right by the major party of the mainstream right raises the odds of an extreme right vote. This suggests that the second hypothesis advanced above (that a mainstream right party may legitimize the policies of the extreme right, and hence lead to the extreme right experiencing greater electoral success) has some validity.

As concerns the distance between the mainstream parties, our findings suggest that the extreme right party vote increases as the distance between the two mainstream parties increases. This being said, however, the coefficient does not pass the conventional threshold of significance (p = 0.08). Thus, although they are suggestive, our data do not provide conclusive evidence as to which of the competing hypotheses advanced above is borne out in practice.

The final medium-term party system variable that we included in our model referred to the coalition format of the party systems under investigation. Our findings in Table 3 show that the existence of a grand coalition government before the election in question does indeed have a substantial effect. As we anticipated, the presence of such a governing coalition raises the odds of voting for the extreme right. Depending on the level of the other variables, the probability of an extreme right vote is roughly doubled.

As concerns the variables that related to short-term contextual factors, Table 3 shows that the effect on the extreme right vote of the number of asylum-seekers is in line with expectations (it is positive), while the coefficient for the change in the number of asylum-seekers is negative. However, both these variables miss the usual threshold for statistical significance by a considerable margin. Therefore, we must assume that their true effect is zero.

The effect of unemployment (as a macro variable) on extreme right voting is markedly negative– that is, the odds of voting for the extreme right fall as the rate of unemployment increases. While this clearly does not allow us to draw any conclusions about the extreme right's appeal to unemployed people (since this would be an instance of ecological fallacy),21 we can surmise that extreme right parties perform better at the polls in societies where unemployment is low. Although similar results have been reported in other studies (e.g., Knigge 1998; Coenders & Scheepers 1998; Lubbers et al. 2002), a substantial explanation for this finding is not readily given. One plausible (yet untested) reason for this negative relationship is that people may turn (back) to the more established and experienced mainstream parties in times of economic uncertainty rather than to the parties of the extreme right that lack such experience (Knigge 1998: 269–270). The coefficient for the change in unemployment is positive, but is not statistically significant, thus again implying that the true impact of this variable on the likelihood of a vote for the extreme right is zero.

In the same way that we summarized the findings of our socio-demographic model in Table 2, Tables 4a and 4b summarize the findings of our complete model and show the combined impact of the four strongest system-level predictors on two segments of the population. Table 4a depicts the expected probability of an extreme right vote of a group that is least likely to support parties the extreme right (female voters, aged 45–54, with university education, and from the ‘unclassified’ class category); and Table 4b shows estimates for a segment of the general population among which the extreme right is usually quite successful (male manual workers, aged 24 or younger, with no or primary education only). Tables 4a and 4b show the expected probability of an extreme right vote from these two types of voters in situations where there is a grand coalition in place in the preceding period of government and when there is not; the disproportionality of the electoral system is 1 (low) and where it is 5 (high); the ideological position of the major party of the mainstream right is −5, −1, 1 and 3 (with −5 indicating a rather left-wing position and 3 indicating a more right-wing position); and the unemployment rate is 2, 4, 6, 8, 10 and 12 per cent.

Table 4a.  Predicted probabilities of an extreme right vote depending on various system-level variables (percentage). Female voters aged 45–54, with university education and from the ‘unclassified’ class category
 Disproportionality: 1Disproportionality: 5
  1. Notes: MR: Major party of the mainstream right (with −5 indicating a rather left-wing position and 3 indicating a more right-wing position). Other system-level variables are held at their respective means, which were calculated giving equal weight to every election. Typical 95 per cent confidence intervals: no grand coalition, unemployment 6 per cent, disproportionality 1, ideological position of major party of the mainstream right −1: 1.3–2.9; grand coalition, unemployment 2 per cent, disproportionality 5, ideological position of major party of the mainstream right 1: 6.9–24.4.

Grand coalition: No
Ideological position of MR−5−113−5−113
Unemployment rate:
235564678
423443456
612232334
811121222
1011111112
1201110111
Grand coalition: Yes
Ideological position of MR−5−113−5−113
Unemployment rate:
26910128121316
4467868911
634554567
823342345
1012222233
1211111122
Table 4b.  Predicted probabilities of an extreme right vote depending on various system-level variables (percentage). Male manual workers, aged 24 or younger, with no or primary education only)
 Disproportionality: 1Disproportionality: 5
  1. Notes: MR: Major party of the mainstream right (with −5 indicating a rather left-wing position and 3 indicating a more right-wing position). Other system-level variables are held at their respective means, which were calculated giving equal weight to every election. Typical 95 per cent confidence intervals: no grand coalition, unemployment 6 per cent, disproportionality 1, ideological position of major party of the mainstream right −1: 10.8–14.5; grand coalition, unemployment 2 per cent, disproportionality 5, ideological position of major party of the mainstream right 1: 47.8–57.7.

Grand coalition: No
Ideological position of MR−5−113−5−113
Unemployment rate:
22026293325323640
41418212417232630
6912141712161921
86810118111315
10467857910
1234453567
Grand coalition: Yes
Ideological position of MR−5−113−5−113
Unemployment rate
23341455040485357
42431353930374246
61722252921283135
81116182115202326
10811121410141618
1257810791113

First, we note that the socio-demographic variables have a considerable and consistent impact even if we control for system-level variables. If we compare equivalent cells from Table 4a and Table 4b, it is obvious that independent of the socio-political context, the probability of an extreme right vote is about five to six times higher for the young male, primary-educated worker than for the middle-aged, unclassified, university-educated female voter. This said, the impact of the system-level variables is considerable, too. Depending on the variable constellation, the presence of a grand coalition government before the election almost doubles the support for the extreme right (to see this we can compare equivalent cells in the upper and lower parts of either Table 4a or 4b). The position of the major party of the mainstream right has almost the same impact: if this party is closer to the empirical right end of our scale (score of 3), the probability of a vote for the extreme right is about 1.5 to 2 times higher than in situations where this party is further to the left (score of −5). To see this effect, we can look at each row and compare the first and the fourth, and the fifth and the eighth cells, respectively. For example, when there is no grand coalition, the disproportionality of the electoral system is 1, the unemployment rate is 2 per cent and the ideological position of the major party of the mainstream right is −5 (i.e. rather left-wing), the probability of an extreme right vote from our female voter is 3 per cent (as shown in bold in the top left cell in the upper half of Table 4a). However, when the ideological position of the party of the mainstream right is 3 (i.e., more right-wing) and all the other conditions stay as before, the probability of our female voter casting her vote for a party of the extreme right is now 6 per cent (as shown in bold in the first row, fourth column in the upper half of Table 4a). By contrast, the effect of disproportionality is rather moderate: the probability of a vote for the extreme right is 1.1 to 1.5 times higher in a situation in which there is high disproportionality (score of 5) than in a situation where disproportionality is low (score of 1). We can see this if we compare the left and the right halves of Tables 4a and 4b.

Finally, our model shows that unemployment has a massive impact on the probability of a vote for the extreme right. An increase of two percentage points in the unemployment rate (e.g., an increase from 4 to 6 per cent) reduces the probability of a vote for the extreme right by between one third and one fifth (depending on the other variables). To see this, we can compare any cell in Table 4a or 4b with the cell directly above or beneath it.

The combined impact of these four system-level variables alone is large – something that becomes obvious if we compare a situation where according to our findings the extreme right should be least successful (i.e., where there is high unemployment, no grand coalition, low disproportionality and where the major party of the mainstream right is far to the left) with a situation where the extreme right is expected to be most successful (i.e., the reverse conditions). In situations where the extreme right is thought to be least successful, our prototypical female voter has an expected probability of voting for the extreme right of (almost) 0 per cent (as shown in bold in the first column, last row of the upper half of Table 4a). By contrast, in situations where the extreme right is thought to be most successful, this same voter has a predicted probability of voting for the extreme right of 16 per cent (as indicated in bold in the last column, first row of the lower half of Table 4a). In other words, when we compare the two situations, the expected probability of an extreme right vote from our female voter varies by a factor of about 40. As for the expected probability of an extreme right vote from our male voters in the two different situations, we expect a support of 3 per cent (as shown in bold in the first column, last row of the upper half of Table 4b) in a situation where the extreme right is expected to be least successful, and a support of 57 per cent in a situation where the extreme right is expected to be most successful (as indicated in bold in the last column, first row of the lower half of Table 4b). The expected probability of an extreme right vote from our male voter thus varies by a factor of roughly 22.

Clearly, these probabilities are open to interpretation as our model does not fit the data perfectly, is based on only 24 elections and might not contain all the relevant system-level predictors. Furthermore, our scenarios are somewhat counterfactual in that in the past all the conditions that according to our model favour the extreme right have never been present simultaneously in one country and neither have all the conditions that seem to hinder the success of the parties of the extreme right. Therefore, in practice, there would probably be a limit to the potential of the parties of the extreme right, whereas our model assumes that the effects of the system-level factors are additive in the logits. This being said, however, even if we take the probabilities estimated by our model as guidelines rather than exact prognoses of an extreme right vote, they nonetheless provide clear testimony of the importance of system-level factors in explaining the probability of an extreme right vote, and hence in accounting for uneven electoral success of the extreme right across the countries of Western Europe.

Conclusion

  1. Top of page
  2. Abstract
  3. Theoretical framework
  4. Data and methodology
  5. Findings
  6. Conclusion
  7. Acknowledgements
  8. References

In the course of our analysis, we have shown that a voter's socio-demographic attributes go a long way towards explaining his or her propensity to vote for a party of the extreme right. Our results – which confirmed many of the conclusions reached in the existing country studies – indicate that being male, young (under 25) and a manual worker significantly raised the probability of voting for the extreme right in all the elections under study, whereas being female, middle-aged and a professional markedly decreased the probability of voting for a party of the extreme right. The only slightly unanticipated result was the finding that voters with middle school levels of education (rather than those with lower levels of education) had the highest propensity to vote for the extreme right.

Although our results provide a good basis for predicting the likelihood of an extreme right vote, socio-demographic characteristics do not go very far in explaining why the parties of the extreme right have encountered greater levels of electoral success in some instances, but have experienced relative failure in others. Therefore, we estimated an augmented model that allowed us to assess the degree to which political opportunity structures account for the variation in the extreme right's vote after individual-level socio-demographic characteristics have been controlled for. The impact of system-level variables is considerable. In particular, our results show that the level of unemployment, the position of the major party of the mainstream right, the disproportionality of the electoral system and the presence of a grand coalition government are particularly important in explaining the uneven success of the right-wing extremist parties across Western Europe. The effects of most of these variables were as we anticipated: we found that the more to the right the mainstream right party, the greater the likelihood of an extreme right vote being cast, suggesting that a right-wing mainstream party may have a legitimizing effect on the policies of the extreme right. Our findings also showed that the presence of a grand coalition government prior to elections raises the odds of an extreme right vote being cast, most probably because levels of voter dissatisfaction are higher during periods of grand coalitions than during periods of alternating government.

By contrast, some of our other results were not as we expected: we found that the coefficient for the disproportionality of the electoral system was in fact positive, rather than negative as we had assumed, suggesting that right-wing extremist voters are not responding to the psychological effects of electoral systems in the way we might expect. In addition, the effect of unemployment (as a macro variable) was markedly negative, rather than positive as we had expected, perhaps because voters turn (back) to the more experienced mainstream parties in times of high unemployment.

We believe that above and beyond their academic worth, our findings have implications for the real world. In particular, they suggest that the ring-wing extremist vote will not be curbed by simply looking after economic conditions. They also indicate that tampering with electoral systems (to render them less proportional) might not lead to lower extreme right party scores. Furthermore, our results imply that, in the West European case at least, a move to the right by a party of the mainstream right is more likely to legitimize the extreme right than quell the demand for the latter's policies. These findings thus go some distance towards challenging the conventional wisdom as to how the advance of the parties of the extreme right may be halted.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Theoretical framework
  4. Data and methodology
  5. Findings
  6. Conclusion
  7. Acknowledgements
  8. References

We would like to thank members of the Extreme Right Electorates and Party Success (EREPS) research group, as well as Martin Elff, Tony Mughan, Thomas Poguntke and Harald Schoen for helpful comments and suggestions on earlier versions of this article. We are also grateful to Kris Deschouwer and to two anonymous referees for their very useful feedback. Finally, we would like to acknowledge the financial support we received from the British Academy and the French CNRS.

Notes
  • 1

    Their data contain a very low number of level two units (countries). According to much of the literature, the number of level two units should be at least 30 (Snijders & Bosker 2000: 140; Hox 2002: 173–179), and if one is interested in the variance components (as Lubbers et al. are), then this number should be even higher (Hox 2002: 175).

  • 2

    We do not incorporate the positions of the parties of the extreme right in our model because we are interested above all in the space available to the right-wing extremist parties, because including both space and positions would lead to problems of multicollinearity and because some of these parties are not included in the CMP data.

  • 3

    Although the position of the major party of the mainstream right and the ideological convergence between the two major parties are conceptually related, the empirical correlation between both measures is negligible (r = −0.18).

  • 4

    See the EREPS homepage: http://www.politik.uni-mainz.de/ereps/.

  • 5

    Austria and Italy are missing from the CSES data set, and the coverage for Denmark and Germany only starts in 1998.

  • 6

    Since all our Belgian extreme right voters voted for the Vlaams Blok, our party system variables relate to the Flemish party system.

  • 7

    Despite our best efforts, we were forced to exclude Sweden, the Netherlands and Switzerland from our analysis as we were unable to access national election studies in these countries.

  • 8

    There is substantial agreement within the literature that following the Fiuggi Congress in 1995, the AN gradually became a part of the mainstream right (Newell 2000). In light of this, the post-1995 AN is not included in our analysis.

  • 9

    Three of the elections under study (Austria 1999, Belgium 1999 and Norway 2001) took place after the CMP data were gathered. For these, we made use of the positions of the parties at the most recent election for which CMP data do exist.

  • 10

    The empirical minimum is −12.4 (the Norwegian Socialists in the 1990s) and the empirical maximum for a party of the moderate right is 20.4 (the position of the Danish KF in the 1990s). However, the major mainstream right parties usually register much lower scores – e.g., the Austrian ÖVP's score in 1994 was 3.6 and the French RPR's score in 1997 was 3.3.

  • 11

    For aggregate level data, see LABORSTA (http://laborsta.ilo.org) and Statistics Norway (http://www.ssb.no/English/subjects/06/01/aku_en/).

  • 12

    Data for 2001 were obtained from UNHCR (http://www.unhcr.ch); data for all other years are from OECD-SOPEMI (OECD 1992, 2001).

  • 13

    We chose to use this figure because when asked about ‘foreigners’, the majority of citizens in the countries under study think of people from outside Western Europe (Fuchs et al. 1993) and because the alleged ‘flood’ of refugees and asylum-seekers from outside Western Europe became the main target of the extreme right's appeals in the countries under study.

  • 14

    Variations in the ideology of the extreme right could be seen as the exception to this statement. However, since information on their position is not available for all parties and elections (see Note 2) and since we are primarily concerned with exogenous conditions for their success, we treat all variation in the strength of the effects as random error.

  • 15

    Throughout this article, we report ‘robust’ standard errors that correct for heteroscedasticity and adjust for correlated disturbances within countries. They thereby yield very conservative t-statistics and confidence intervals.

  • 16

    The coefficients for those in the three middle age categories are jointly different from the reference group although two of them fail individual significance tests.

  • 17

    The last three coefficients are jointly significant although they fail the individual tests.

  • 18

    The one notable exception to this is the coefficient for no/primary education, which is now closer to the coefficient for middle school.

  • 19

    The BIC reflects the trade-off between model fit and loss of degrees of freedom. A difference of 10 or more is regarded as lending very strong support to the model with the smaller BIC.

  • 20

    This variable reflects the disproportionality score of the previous election.

  • 21

    Unfortunately individual unemployment it is not consistently recorded in the surveys.

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  3. Theoretical framework
  4. Data and methodology
  5. Findings
  6. Conclusion
  7. Acknowledgements
  8. References
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