Abstract
Citizen support for political institutions is a key component of any representative democracy. Two main approaches to explain political support can be found in the relevant literature: (i) Socio-cultural theories assume that political support is politically exogenous and emphasize factors such as social trust when explaining political support. (ii) Proponents of performance-based explanations, in contrast, see political support as primarily driven by politically endogenous factors, such as people's experiences of political authorities and institutions and evaluations of their performance. In this article I argue that the earlier research has missed an important source of interaction between these two sets of explanatory factors. More precisely, I hold that generalized or social trust plays a central but hitherto misunderstood role in explaining political support. The main hypothesis states that the effects on political support of performance-related factors are greater among low trusters compared to high trusters. I test this interaction hypothesis in a multilevel model, using cross-national survey data from 23 European countries. The results strongly confirm the stated hypothesis.
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Notes
The concept is not only multidimensional but also goes by many names in the literature: political support, political trust, institutional trust and institutional confidence, to mention just a few. In this article I will mainly use the term ‘political support’. For the sake of variation I will sometimes use the other terms interchangeably. But they all refer to the same theoretical concept; the middle levels of political support Norris (1999a) refers to as support for regime institutions.
For good overviews of different explanations of political support, see Mishler and Rose (1997), Nye (1997), Norris (1999b), Levi and Stoker (2000), Newton and Norris (2000), Mishler and Rose (2001), Denters et al (2006).
However, it should be noted that Zmerli and Newton (2008) in a recent study report robust and statistically significant relationships between social trust and confidence in political institutions within 23 European countries and in the United States.
A person low in generalized trust may, of course, act as a moralistic truster toward those near and dear to him/her.
Data and fieldwork documentation are available at www.europeansocialsurvey.org/. These cross-section data sets consist of nationally representative samples of individuals in 23 countries. The survey design includes strict quality controls, such as random probability sampling, a minimum target response rate of 70 per cent and rigorous translation protocols.
The countries included in the merged data set are: Austria, Belgium, the Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Israel, Italy, Luxembourg, the Netherlands, Norway, Poland, Portugal, Slovenia, Spain, Sweden, Switzerland and the United Kingdom.
The eigenvalue for the first component is 2.55. The single component explains 64 per cent of the total variance.
Cronbach's α for the resulting scale is reassuringly high (0.81).
Earlier empirical studies have used more direct measures of membership and activity in voluntary organizations when testing the influence of people's embeddedness in social networks (Denters et al, 2006; Espinal et al, 2006). Unfortunately, detailed items tapping organizational involvement are included only in the first round of ESS. Preliminary tests, however, show that the hypothesis of this study are supported also when restricting the sample to the first round of ESS and employing a measure of membership across a large set of different voluntary organizations.
Unfortunately, the ESS data set offers very few possibilities for directly testing the implications for political support of Inglehart's theory of modernization and value change. However, an indirect and crude way of controlling for these effects is to include age in the models as a regressor (Inglehart, 1999).
Because of lack of data for the Eastern European countries the remaining two factors – executive dominance and number of issue dimensions – are excluded from the consensus/majority index. However, it should be noted that the correlation between Lijphart's original measure and the adapted version used in this study is comfortingly high – r=0.98.
Sample max/min for the three country-level variables are Switzerland 2004/Great Britain 2004 (majoritarian-consensus index); Finland 2004/Greece 2004 and Poland 2004 (corruption); and Norway 2004/Poland 2004 (misery).
See Snijders and Bosker (1999) and Steenbergen and Jones (2002) for accessible introductions to multilevel modeling techniques.
However, it is worth pointing out here that the relative strength of the effects of various variables coded along the same scale depends both on the size of the coefficient estimates and on the relative distributions of the variables. Looking at the standard deviations of the five indicators of performance-related factors it is obvious that they differ in their relative distributions. Whereas the standard deviations of the two variables tapping evaluations of economic and political performance and the safety indicator are all close to 0.25 the spread of the variables measuring whether the respondent has been exposed to crime and his/her affinity with the ruling party is significantly larger (the standard deviations equal 0.41 and 0.48, respectively). But even when taking the lower variance of the two evaluation indicators into consideration we can still conclude that their relative impact on political support is considerably greater compared to the effects of the other three performance-related factors. I would like to thank an anonymous reviewer for pointing this out.
The three bivariate zero-order correlations amount to 0.71 (between corruption and misery); 0.22 (between corruption and majoritarianism); 0.26 (between misery and majoritarianism).
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Appendix
Appendix
Survey items
Satisfaction with democracy. ‘How satisfied are you with the way democracy works in [country R]?’ ‘Extremely dissatisfied’=0; ‘Extremely satisfied’=10.
Trust in parliament. ‘How much you personally trust [country R]'s parliament?’ ‘No trust at all’=0; ‘Complete trust’=10.
Trust in the legal system. ‘How much you personally trust the legal system?’ ‘No trust at all’=0; ‘Complete trust’=10.
Trust in the police. ‘How much you personally trust the police?’ ‘No trust at all’=0; ‘Complete trust’=10.
National economic performance. ‘How satisfied are you with the present state of the economy in [country R]?’ ‘Extremely dissatisfied’=0; ‘Extremely satisfied’=10.
Health service performance. ‘Please say what you think overall about the state of health services in [country R] nowadays?’ ‘Extremely bad’=0; ‘Extremely good’=10.
Crime victim. ‘Have you or a member of your household been the victim of a burglary or assault in the last five years?’ ‘No’=0; ‘Yes’=1.
Neighborhood safety. ‘How safe do you – or would you – feel walking alone in this area after dark?’ ‘Very safe’=1; ‘Very unsafe’=4.
Political winner/loser. ‘Which party did you vote for in the last national election?’ If party choice matches a governing party=1; if opposition party=0.
Generalized trust. ‘Generally speaking, would you say that most people can be trusted, or that you can’t be too careful in dealing with people?’ ‘You can’t be too careful’=0; ‘Most people can be trusted’=10.
Social activity. ‘Compared to other people of your age, how often would you say you take part in social activities?’ ‘Much less than most’=1; ‘Much more than most’=5.
Church attendance. ‘Apart from special occasions such as weddings and funerals, about how often do you attend religious services nowadays?’ ‘Every day’=1; ‘Never’=7.
Education. Years of full-time education.
Gender. ‘Male’=0; ‘Female’=1.
Majoritarian. A version of Lijphart's (1999) index of consensus and majority systems. Data taken from Lijphart (1999, p. 312) except for the Czech Republic, Estonia, Hungary, Poland and Slovenia where data from Klaus Armingeon's data set ‘Comparative Political Dataset II (28 Post-Communist Countries)’ are used. For the Czech Republic, Estonia, Hungary, Poland and Slovenia the variable is based on data for the period 1992–2002. All calculations according to Lijphart (1999, p. 247).
Corruption. Corruption index from International Country Risk Guide as of the year of the survey. The index ranges between 0 and 6 where lower values denote more corrupt countries.
Misery index. Standardized unemployment rates from OECD and ILO as of the year of the survey. Inflation rates from World Development Indicators.
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Oskarsson, S. Generalized trust and political support: A cross-national investigation. Acta Polit 45, 423–443 (2010). https://doi.org/10.1057/ap.2010.3
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DOI: https://doi.org/10.1057/ap.2010.3