| Literature DB >> 29187802 |
Matthijs Rooduijn1, Brian Burgoon2, Erika J van Elsas3, Herman G van de Werfhorst4.
Abstract
Support for radical parties on both the left and right is on the rise, fueling intuition that both radicalisms have similar underpinnings. Indeed, existing studies show that radical left and right voters have overlapping positions and preferences. In this article, however, we focus on the differences in the voting bases of such parties. We show that radical left and right voters have sharply diverging ideological profiles. When it comes to the historical traditions of the 'left' and 'right', these voters differ radically from each other. Both groups express the traditions associated with their mainstream counterparts-particularly with respect to (non-)egalitarian, (non-)altruistic, and (anti-)cosmopolitan values. Such differences also explain why radical left voters tend to be more, not less, educated than mainstream or radical right voters.Entities:
Keywords: Radical left; radical right; voting behavior
Year: 2017 PMID: 29187802 PMCID: PMC5697563 DOI: 10.1177/1465116517718091
Source DB: PubMed Journal: Eur Union Polit ISSN: 1465-1165
Selected countries and parties.
| Country | Radical right party | Radical left party |
|---|---|---|
| Austria | FPÖ, BZÖ | |
| Belgium | VB, FNb | |
| Bulgaria | ATAKA | |
| Cyprus | AKEL | |
| Czech Republic | KSCM | |
| Denmark | DF | EL, SF |
| Finland | PS | VAS |
| France | FN, MNR | PCF, LO, LCR |
| Germany | Republikaner, NPD | Linke |
| Greece | LAOS | KKE, SYN |
| Hungary | Jobbik, MIEP | MP |
| Ireland | SF | |
| Italy | LN, AN | PRC, Comunisti |
| Netherlands | LPF, PVV | SP |
| Norway | Rodt, SV | |
| Poland | LPR | |
| Portugal | PCP, BE | |
| Slovenia | SNS, LIPA | |
| Slovakia | SNS | KSS |
| Spain | IU | |
| Sweden | SD | V |
| Switzerland | SVP | |
| United Kingdom | BNP, UKIP |
Logistic regression models estimating radical right and radical left support.
| Mainstream (0) vs. Radical Right (1) | Mainstream (0) vs. Radical Left (1) | |||||||
|---|---|---|---|---|---|---|---|---|
| (1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | |
| Education | 0.711*** | 0.787*** | 0.883*** | 0.883*** | 1.023 | 1.114*** | 1.090*** | 1.097*** |
| (0.019) | (0.019) | (0.019) | (0.022) | (0.022) | (0.022) | (0.022) | (0.023) | |
| Religious | 0.946*** | 0.944*** | 0.952*** | 0.953*** | 0.804*** | 0.806*** | 0.807*** | 0.806*** |
| (0.010) | (0.010) | (0.010) | (0.012) | (0.017) | (0.016) | (0.016) | (0.022) | |
| Age | 0.979*** | 0.982*** | 0.978*** | 0.978*** | 1.001 | 1.003 | 1.004 | 1.004 |
| (0.003) | (0.003) | (0.003) | (0.003) | (0.003) | (0.003) | (0.003) | (0.003) | |
| Urban | 0.837** | 0.839** | 0.892 | 0.887 | 1.168** | 1.144** | 1.133 | 1.139 |
| (0.047) | (0.047) | (0.053) | (0.064) | (0.058) | (0.057) | (0.056) | (0.082) | |
| Female | 0.727*** | 0.747*** | 0.694*** | 0.683*** | 1.093 | 1.065 | 1.074 | 1.086 |
| (0.049) | (0.050) | (0.051) | (0.063) | (0.052) | (0.055) | (0.055) | (0.058) | |
| 2 (man.superv. And skilled) | 0.992 | 0.968 | 0.920 | 0.913 | 0.914 | 0.968 | ||
| (0.083) | (0.082) | (0.104) | (0.067) | (0.067) | (0.096) | |||
| 3 (self-empl.) | 0.811 | 0.841 | 0.809 | 0.559*** | 0.553*** | 0.573*** | ||
| (0.093) | (0.089) | (0.094) | (0.051) | (0.050) | (0.060) | |||
| 4 (routine non-manual) | 0.748*** | 0.852 | 0.864 | 0.797** | 0.779** | 0.844 | ||
| (0.053) | (0.059) | (0.087) | (0.067) | (0.066) | (0.079) | |||
| 5 (lower controller) | 0.610*** | 0.692*** | 0.673*** | 0.789** | 0.762*** | 0.763** | ||
| (0.042) | (0.046) | (0.054) | (0.059) | (0.058) | (0.068) | |||
| 6 (higher controller) | 0.482*** | 0.557*** | 0.546*** | 0.671*** | 0.653*** | 0.697 | ||
| (0.047) | (0.046) | (0.052) | (0.076) | (0.076) | (0.104) | |||
| Income (subjective) | 0.800*** | 0.880** | 0.894 | 0.666*** | 0.654*** | 0.629*** | ||
| (0.038) | (0.040) | (0.057) | (0.029) | (0.028) | (0.032) | |||
| Unemployed | 1.374 | 1.352 | 1.458 | 1.205 | 1.235 | 1.347** | ||
| (0.286) | (0.264) | (0.391) | (0.107) | (0.110) | (0.137) | |||
| Anti-immigration | 1.568*** | 1.472*** | 0.915*** | 0.879*** | ||||
| (0.016) | (0.022) | (0.022) | (0.028) | |||||
| Anti-EU | 1.153*** | 1.073*** | ||||||
| (0.021) | (0.023) | |||||||
| Constant | 1.916 | 2.854** | 0.106*** | 0.070** | 0.013*** | 0.030*** | 0.053*** | 0.082*** |
| (0.562) | (0.979) | (0.034) | (0.027) | (0.013) | (0.029) | (0.052) | (0.077) | |
| Observations | 57,269 | 57,269 | 57,269 | 36,027 | 54,388 | 54,388 | 54,388 | 33,536 |
|
| 0.170 | 0.179 | 0.253 | 0.272 | 0.074 | 0.089 | 0.092 | 0.097 |
Clustered standard errors; entries are odds ratios.
p < 0.05, **p < 0.01, ***p < 0.001.
Logistic regression models estimating different dependent variables, including attitudes as independent variables.
| (1) | (2) | (3) | |
|---|---|---|---|
| Radical Right | Radical Left | RR (0) vs. RL (1) | |
| Education | 0.882*** | 1.089*** | 1.280*** |
| (0.021) | (0.023) | (0.052) | |
| Religious | 0.956*** | 0.824*** | 0.935*** |
| (0.010) | (0.016) | (0.017) | |
| Age | 0.978*** | 1.001 | 1.019*** |
| (0.003) | (0.003) | (0.004) | |
| Urban | 0.887 | 1.157** | 1.390 |
| (0.055) | (0.055) | (0.204) | |
| Female | 0.694*** | 0.945 | 1.736*** |
| (0.052) | (0.054) | (0.196) | |
| 2 (man.superv. and skilled) | 0.965 | 0.917 | 0.877 |
| (0.087) | (0.068) | (0.195) | |
| 3 (self-empl.) | 0.856 | 0.628*** | 0.652 |
| (0.093) | (0.055) | (0.167) | |
| 4 (routine non-manual) | 0.867 | 0.786 | 0.690 |
| (0.068) | (0.074) | (0.121) | |
| 5 (lower controller) | 0.697*** | 0.807** | 0.977 |
| (0.046) | (0.067) | (0.162) | |
| 6 (higher controller) | 0.563*** | 0.723** | 1.137 |
| (0.047) | (0.088) | (0.226) | |
| Income (subjective) | 0.898 | 0.780*** | 0.878 |
| (0.043) | (0.028) | (0.095) | |
| Unemployed | 1.343 | 1.077 | 0.552** |
| (0.264) | (0.114) | (0.110) | |
| Anti-immigration | 1.507*** | 0.923*** | 0.568*** |
| (0.016) | (0.016) | (0.073) | |
| Strong govt. | 1.137*** | 0.871*** | 0.766*** |
| (0.029) | (0.023) | (0.037) | |
| Econ. Dissatisf. | 1.059*** | 1.132*** | 1.022 |
| (0.014) | (0.013) | (0.027) | |
| Pol. Distrust | 1.018 | 1.011 | 0.990 |
| (0.013) | (0.012) | (0.028) | |
| Egalitarian | 0.796*** | 1.209*** | 1.546*** |
| (0.023) | (0.025) | (0.078) | |
| Altruist | 0.987 | 1.082 | 0.992 |
| (0.029) | (0.035) | (0.053) | |
| Support Govt. Redist. | 1.011 | 1.741*** | 1.504*** |
| (0.028) | (0.070) | (0.088) | |
| Constant | 0.138*** | 0.001*** | 0.014*** |
| (0.055) | (0.001) | (0.023) | |
| Observations | 54,832 | 51,770 | 7276 |
|
| 0.260 | 0.141 | 0.434 |
Clustered standard errors; entries are odds ratios.
p < 0.05, **p < 0.01, ***p < 0.001.
Logistic regression models estimating the interaction effect of education and altruism on different dependent variables.
| Model 1 Mainstream vs. RR | Model 2 Mainstream vs. RL | |
|---|---|---|
| Education | 0.844 | 0.902 |
| (0.081) | (0.058) | |
| Altruism | 0.958 | 0.934 |
| (0.064) | (0.057) | |
| Education × Altruism | 1.009 | 1.039*** |
| (0.019) | (0.012) | |
| Constant | 0.160*** | 0.002*** |
| (0.085) | (0.002) | |
| Observations | 54,832 | 51,770 |
|
| 0.260 | 0.141 |
Clustered standard errors; entries are odds ratios; control variables are included but not displayed.
**p < 0.001.
Figure 1.Marginal effects of education conditional upon altruism and altruism conditional upon education. Note: The graphs display the marginal effect of education conditional on the level of altruism (Panels a and c), and the marginal effect of altruism conditional on the level of education (Panels b and d).