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The Effect of Inequality on the Relation Between Socioeconomic Stratification and Political Trust in Europe

Abstract

While the relation between inequality and levels of political trust has been intensely investigated, there is no consensus yet on the mechanism behind this relation. In this paper, we use multilevel models to analyse the diverging impact of economic inequality on political trust for different social groups within European countries. We observe that changes in inequality are associated with lower levels of political trust across all social strata, as operationalised through income level, education and employment status. In more unequal societies, differences in political trust between social strata are also smaller. In equal countries, on the other hand, well-off citizens are clearly more trusting than their less well-off counterparts. Altogether, the study contributes to discussions about the determinants of political support and how citizens are connected to their political system in an era of rising inequality, by suggesting the presence of a social justice frame. The analyses are based on the European Social Survey (2002–2016).

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Notes

  1. 1.

    We will study 28 countries, for which we have full information available in the main models of the article (i.e. Tables 1 and 2). The individual N depends on the models specifications.

  2. 2.

    Replicating the analyses with a broader indicator of institutional trust (with trust in the legal system and police included within the mean-score) does not alter the results given the strong internal coherence of the political trust scale.

  3. 3.

    The Cronbach’s alpha of the political trust scale for 2002 is 0.809 and for the 2004–2016 waves is 0.907.

  4. 4.

    When interpreting the association between this indicator and political trust, it should be taken into account that other socio-psychological processes might be at play here, that define how economically satisfied an individual reports to be (e.g., because of diverging processes of social comparison or relative deprivation between countries). .

  5. 5.

    Eurostat operationalises this indicator in the following manner: “This indicator corresponds to the sum of persons who are: at risk of poverty after social transfers, severely materially deprived or living in households with very low work intensity. Persons are counted only once even if they are affected by more than one of these phenomena. Persons are considered to be at risk of poverty after social transfers, if they have an equivalised disposable income below the risk-of-poverty threshold, which is set at 60% of the national median equivalised disposable income” (Eurostat, 2018c). .

  6. 6.

    As we are using Eurostat data, we miss information for some non-EU member countries: Albania, Israel, Russia, Ukraine and Kosovo. Similarly, for the OECD data, some country level information is missing too: Bulgaria, Croatia, Cyprus, Kosovo, Romania, Russia, Switzerland and Ukraine.

  7. 7.

    Expressed in euros and controlled for purchasing power parity.

  8. 8.

    We have missing information for Israel, Kosovo, Russia, Turkey and Ukraine on the GDP per capita indicator.

  9. 9.

    Note that the within variation is always smaller than the between variation.

  10. 10.

    Before starting the analyses, we tested whether the errors of our country level variables were independently distributed (which we would expect if the data were drawn from a random sample). This was indeed the case (residual plots available on request): the residual pattern did not suggest any obvious reason to be concerned about the consequences of the fact that we rely on a non-random sample.

  11. 11.

    Analysing the different operationalisations of socioeconomic status together in one model does not lead to problems with multi-collinearity: the VIF-scores of the variables were never higher that 3 (tested on pooled data).

  12. 12.

    Model 4, which includes the interaction term with and random slope for economic satisfaction reports a slightly different coefficient: (β = 0.22, p < .001).

  13. 13.

    We checked for all inequality variables whether there was sufficient within variation (versus between variation) before constructing our orthogonal terms. In the case of the P90/P50 variable, there was hardly any within-country variation in the indicator. Therefore, we only analyse the countrywide average (cfr. the “between” variation) of this variable.

  14. 14.

    The interaction coefficients with the within inequality indicators were mostly non-significant.

  15. 15.

    This statement is applicable both when analysing models that include or exclude the interaction effects.

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Goubin, S., Hooghe, M. The Effect of Inequality on the Relation Between Socioeconomic Stratification and Political Trust in Europe. Soc Just Res (2020). https://doi.org/10.1007/s11211-020-00350-z

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Keywords

  • Economic inequality
  • Political trust
  • Socioeconomic status
  • Political legitimacy
  • Political support
  • European Social Survey