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The Meaning of Democracy to Citizens Across European Countries and the Factors Involved

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Abstract

What do citizens think democracy is and what factors contribute to its meaning? Previous works on the public understanding of democracy have shown that, overall, citizens see democracy in “minimal” terms. However, advanced democracies are complex and encompass several elements other than elections and freedoms. This article uses the European Social Survey module “Europeans’ understandings and evaluations of democracy” and multilevel item response theory models to build a measure of the meaning of democracy in terms of multiple attributes and to account for individual- and country-level variation. The findings show that the meaning of democracy can be seen as a continuum, and that middle-aged educated men who are interested in politics, have extreme ideological positions, and are engaged in civic organizations include more elements in their idea of democracy, and that the cross-country variation in the meaning of democracy mostly depends on democratic performance.

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Notes

  1. See Goertz (2006) regarding the contrast between “extension” and “intension” of concepts.

  2. Belgium, Bulgaria, the Czech Republic, Denmark, Estonia, Finland, France, Germany, Great Britain, Hungary, Ireland, Italy, Lithuania, the Netherlands, Norway, Poland, Portugal, Spain, Sweden, Slovenia, Slovakia and Switzerland. Albania, Kosovo, Russia, and Ukraine were excluded as non-democracies (Freedom House 2015). Ideas of democracy in consolidating or in non-democratic regimes may depend on a “logic of learning”, deriving from experience with actual democracy (Dalton et al. 2007). Israel was excluded as a non-European country, while Cyprus and Iceland, as small democracies.

  3. The tenth attribute included in the conceptualization—satisfaction with democracy—is not considered, as it is not a component of democracy, but rather an evaluation.

  4. The ESS includes an item measuring “responsiveness to the citizens” (see Morlino and Quaranta 2014 on responsiveness), which however presents a high number of missing values as it is preceded by a filter question.

  5. The ESS includes an item measuring “freedom of expression”. As for the case of responsiveness, this item is introduced by a filter question, which leads to a high number of missing values.

  6. See the next section on dimensionality.

  7. On this point, see also Quaranta (2013).

  8. An alternative strategy would be changing the threshold for such dichotomization, with the consequence of not being able to identify necessary attributes of democracy. However, it has been shown that changing the threshold does not improve the scale, indicating that under-reporting due to the potential avoidance of extreme responses seems not to be a problem (Kriesi et al. 2016).

  9. Others find as well that the meaning of democracy is unidimensional (see Ariely 2015).

  10. Respondents between 18 and 80 years old are selected.

  11. Inflation is measured as the year-on-year percentages change in average consumer prices; unemployment is measured as the number of unemployed persons as a percentage of the labour force; deficit/surplus is measured as government revenue minus total expenditure as a percentage of the Gross Domestic Product; growth is measured as the annual percentage growth rate of GDP. See Khramov and Lee (2013) for further details. Data come from the International Monetary Fund (2014) and the European Commission (2013).

  12. All variables are measured in 2010.

  13. See Vermunt (2003) and Bacci and Gnaldi (2015) for an alternative multilevel IRT approaches based on discrete latent traits.

  14. The following model could also be estimated as linear (Clinton and Jackman 2009).

  15. The discrimination parameter \(\beta _{j1}\) is constrained to be positive (Fox 2010).

  16. The “direct” aspect of democracy, referendums, is not assigned to any testlet.

  17. See also Fox (2010, 127–130). A similar case is presented in Bafumiet al. (2005), where it is suggested that \(\beta _{j1}\) or \(\beta _{j2}\) can be modelled via a hierarchical prior to account for the item characteristics.

  18. For an introduction see Jackman (2009).

  19. The testlets are assumed to be independent (Fox 2010).

  20. In the Bayesian framework \(\xi _i\) is treated as a missing data, and the equation (2) as a series of regressions for the missing variable (Jackman 2000).

  21. The hyperparameter \(\sigma _{\xi }\) would be redundant if no hierarchical information were included in the model, as it would be fixed at 1 (see Clinton and Jackman 2009).

  22. The model is unidentified. To identify it \(\xi _{ik}\) is normalized so that \(\xi _{ik}^{*} = (\xi _{ik} - c)/m\), where \(c = \bar{\xi }_{ik}\) and \(m = sd(\xi _{ik})\). This normalization has consequences for the parameters \(\beta _{j1}\) and \(\beta _{j2}\), which are transformed as follows: \(\beta _{j1}^{*} = \beta _{j1}m\); \(\beta _{j2}^{*} = \beta _{j2} - \beta _{j1}c\). The term \(\sigma _{\xi }\) is transformed into \(\sigma _{\xi }^{*} = \sigma _{\xi }/m\) and the term \(\sigma _{\eta }\) is transformed into \(\sigma _{\eta }^{*} = \sigma _{\eta }/m\). The individual- and country-level coefficients have to be transformed as well. The intercept \(\gamma\) is transformed into \(\gamma ^{*} = (\gamma - c)/m\); the individual-level coefficients become \({\varGamma }^{*} = {\varGamma }/m\); the country random-effects become \(\eta _{k}^{*} = \eta _{k}/m\); and the country-level coefficients become \(Z_{k}^{*} = Z_{k}/m\). These transformations are possible as they do not change the likelihood, given that \(\beta _{j1}\xi _i - \beta _{j2} = \beta _{j1}^{*}\xi _{ik}^{*} - \beta _{j2}^{*}\). On model identification see Bafumiet al. (2005) and Clinton and Jackman (2009).

  23. MCMC estimation has also been argued to produce more precise estimates when the level-2 units are not numerous (Stegmueller 2013). It also allows borrowing strength through exchangeability (Jackman 2009).

  24. The models are estimated using JAGS (Plummer 2012). Standard diagnostics are used to assess the convergence of the chain. One chain is run, preferring the strategy of “one long chain” over “shorter multiple chains”, as convergence issues are often a matter of inefficiency rather than of number of chains (Jackman 2009, 255–256). The chain is run for 50000 iterations with a burn-in period of 10000 and a thinning of 5, yielding 10000 MCMC draws. Blocking is used.

  25. The numerical values are reported in the Appendix.

  26. The intraclass correlation coefficient is 0.120 (95 % c.i. 0.067; 0.206).

  27. Expected values are computed at the means of the covariates.

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  1. Department of Political Science, LUISS “Guido Carli”, Via di Villa Emiliani 14, 00135, Rome, Italy

    Mario Quaranta

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Quaranta, M. The Meaning of Democracy to Citizens Across European Countries and the Factors Involved. Soc Indic Res 136, 859–880 (2018). https://doi.org/10.1007/s11205-016-1427-x

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