Abstract
The ongoing rise of inequality and the outbreak of the economic crisis since 2008 have fueled the debate about the effects of macro-economic processes on democracy in general, and on political participation in particular. Whereas the effect of economic disparity is well documented in the literature, the implications of the economic downturn have not been sufficiently evaluated so far. The article addresses this gap by offering a comprehensive overview of the impact of these macro-economic factors on individual political participation in Europe. Using data from the first six rounds of the European Social Survey, it shows that income inequality reduces participation and enlarges the participatory gap between better- and worse-off. In contrast, economic contraction has no effect on the overall level of participation and makes the poor participate more and the rich less.
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Notes
Taking into consideration only the GDP per capita annual growth (%) without controlling it for the overall level of wellbeing (e.g., GDP per capita itself) overestimates the economic conditions of some fast developing countries (e.g., Estonia) as compared to rich ones (e.g., Finland).
Differently from Kern et al. (2015), we exclude those countries that are rated either as not free or partly free by Freedom House, i.e., Albania, Russia, Turkey, Ukraine and Kosovo. The reason for this is that participating to political affairs may acquire a totally different meaning in full democracies and in authoritarian or semi-authoritarian regimes. Furthermore, we must exclude from the analysis all those countries where the ESS question on income is not included (Bulgaria 2008, Estonia 2004 and 2006, Cyprus 2006 and 2008, Hungary 2002 and 2006, France 2002, Ireland 2002, Portugal 2010 and Slovakia 2008).
Economic Crisis Index = GDP Growth-Unemployment + Deficit-Surplus. For the sake of clarity, we then reverse the scale, so that higher scores correspond to more severe economic hardship. We created the measure by first standardizing the three variables that it includes and then by subtracting gdp growth from the sum of budget deficit and unemployment rate.
Although we have not found any theoretical leads in the literature to suggest that austerity might influence whether income inequality enhances or mitigates the participation gap between the rich and poor, we nonetheless checked for this possibility by running a model with a three-way interaction between economic crisis, income inequality and individual income and a two-way interaction between economic crisis and income inequality. The effects of these interactions turned out to be insignificant (results can be obtained from the authors upon request). Hence we only report the results of the more parsimonious models (i.e., Models 1 and 2).
We are referring here to the predicted probabilities computed on the basis of the regression coefficients. In Binomial Multilevel Models, the coefficient β associated to each X n is the effect of a unit increment of X on the logit scale (i.e., log-odds, or the natural logarithm of the odds determining the probability of a certain outcome Y associated to X). The probabilities are computed by assigning different scores for the variable under scrutiny, holding all other variables constant at their mean value and dummy variables at 1 (for more on predicted probabilities, please see Afshartous and de Leeuw 2005; Skrondal and Rabe-Hesketh 2009).
Three meaningful categories are built on the basis of the years of full-time education completed in order to include approximately 30% of the respondents in each.
A table showing the variation in the four outcomes across different levels of inequality and economic crisis can be obtained from the authors upon request.
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The original version of this article was revised: June 2017. The original was initially published electronically on the publisher’s internet portal (currently SpringerLink) on 18th April 2017, with the Table 1 and Figures 1, 2, 3, 4, 5, 6, 7 & 8 appearing in the incorrect positions. This has since then been amended.
Appendix 1: Descriptive statistics
Appendix 1: Descriptive statistics
Variable | Number of observations | Mean | Standard deviation | Min | Max |
---|---|---|---|---|---|
Dependent variable | |||||
Voted | 245.479 | .778 | .416 | 0 | 1 |
Worked in organization | 212.011 | .038 | .191 | 0 | 1 |
Boycotted products | 211.534 | .182 | .386 | 0 | 1 |
Signed petitions | 211.563 | .255 | .436 | 0 | 1 |
Individual-level variables | |||||
Education | 212.519 | 2.050 | .808 | 1 | 3 |
Female | 212.355 | .527 | .499 | 0 | 1 |
Age | 211.409 | 47.80 | 18.499 | 14 | 99 |
Born in another country | 212.373 | .079 | .271 | 0 | 1 |
Religiosity | 211114 | 4.61 | 3.036 | 0 | 10 |
Income | 212.519 | .518 | .499 | 0 | 1 |
Country-year variables | |||||
Gini coefficient | 130 | 30.211 | 3.444 | 22.10 | 39.20 |
GDP per capita | 130 | 33497.910 | 14033.673 | 4455.70 | 101563.70 |
Economic crisis index (ECI) | 130 | 10.231 | 7.832 | −17.80 | 63.30 |
Country variable | |||||
Post-communism | 29 | 0.292 | 0.460 | 0 | 1 |
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Filetti, A., Janmaat, J.G. Income inequality and economic downturn in Europe: a multilevel analysis of their consequences for political participation. Acta Polit 53, 327–347 (2018). https://doi.org/10.1057/s41269-017-0053-1
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DOI: https://doi.org/10.1057/s41269-017-0053-1