Social trust and responses to political
and economic transformation in East-Central Europe*
Natalia Letki and Geoffrey Evans
Nuffield College
Oxford OX1 1NF
natalia.letki@nuffield.oxford.ac.uk
Nuffield College Politics Working Paper 2002-W9
*Earlier version of this manuscript was presented at the symposium
Trust As A Pre-Condition To Communication, Social Thinking And Social Practices During
Democratic Transition In Post-Communist Europe,
British Academy, London 13-15 September 2001
1
Abstract
Social trust forms a major component of current conceptions of social capital
and as such has been attributed a significant role in providing the social context
for the emergence and maintenance of stable, liberal democratic polities and
effective economies. Its role in these processes has in turn been generalized to
post-communist societies in East Central Europe undergoing ‘dual transitions’
from authoritarian states with command economies to democratic free market
societies. In this paper, however, we show that the relations between trust and
perceptions of democratic functioning in Eastern Europe imply a rather
different ‘top-down’ process, in which levels of trust reflect rather than
influence the effectiveness of political and economic institutions. This calls into
question the generalization of models developed in democratic societies to the
post-communist context and provides the basis for an alternative understanding
of the process of social capital formation.
Introduction: Social trust in East-Central Europe
In recent years the post-communist transformation has become a topic of major
significance in political science and sociology. A substantial part of the debate on the
transformation has been devoted to considerations of ‘civil society’. Civil society, defined
generally as a sphere of social organisation occupying the space between the state and the
market, has been acclaimed not only for its role in abolishing the communist systems, but also
because “the concept of civil society may … be regarded as containing elements necessary, if
not sufficient, for the development of the liberal-democratic basis of modern -- or ‘post-modern’
-- socio-economic life” (Miller 1992). A central focus of scholarly interest in developments in
the region has thus concerned the benefits of active civic association and the development of
non-governmental organisations for the emergence of liberal democracy. In this respect,
academic and journalistic attention has been captured by Robert Putnam’s general theory of the
link between civil society and workings of democracy. In his Making Democracy Work (1993)
Putnam stressed the importance of ‘concerted action’ for the condition of democracy, but he
focused not on the explicit principles of participatory democracy, but on their ‘by-products’, i.e.
norms of generalised reciprocity and trust. In his most recent work Putnam insists that social
trust is learned from participation in various types of associations. Social trust and associational
membership form ‘social capital’, which is fundamental to the development of political
institutions as well as economic activity (Putnam 1995a, b, 2000).
The novelty of the social capital approach in the version advocated by Putnam,
Inglehart and others, results from supplementing networks and organisational activities (i.e.
voluntary associations) with a system of norms (i.e. trust and reciprocity). Thus, the discussion
about social trust in ECE forms a natural continuation of the debate about civil society in postcommunist countries, but with more stress placed on a “moral resource” (Putnam 1993: 169)
2
rather than on any type of activity. And although both networks and trust are the components of
social capital, some authors emphasise the superiority of social trust over participatory
behaviour: “civic networks may enhance social life, but this “social connectedness” … is
distinct from – and secondary to – moral values.” (Uslaner 1999: 122).
The concept of social capital has gained such popularity not only because it refers to
ever popular and reputable notions of civic virtues, tolerance and pluralism, but foremost
because it offers an explanation for the flourishing of political and economic systems. As
Jackman and Miller point out, the recent discussion of social capital treats social trust, norms
and reciprocity as “exogenous factors in generating economic and governmental performance”
(1998: 50). And thus, enthusiasts of cultural explanations put forward a list of reasons why
institutional effectiveness hinges on norms and networks. Some of these refer to rational choice
arguments of the positive effects of social trust, such as the reduction of transaction costs and
increased predictability of cooperation, resulting from the belief that cooperation is more
advantageous than individualism (Putnam 1993, Uslaner 1999). Thus Boix and Posner (1998)
point to five dimensions of the positive influence of social capital on government: the relation
between the articulation of citizens’ interests and expectations and the political elite’s
responsiveness (verified later as a result of elections); the reduction of costs of policy and rule
implementation; the transformation of citizens’ preferences from particularistic into collectivist;
the increased effectiveness of bureaucracy (trust and reciprocity within agencies); and, leaders’
ability “to make necessary compromises without losing the support of their group members”
(Boix and Posner 1998: 686-93). Links between cultures of trust and tolerance and the quality,
durability and stability of democratic systems have been examined empirically and the results
seem to confirm that social capital is of crucial importance for the development of democratic
systems (Inglehart 1997, 1999).
Social trust and norms of reciprocity have also been considered to be essential for the
development of civic engagement. Networks of civic participation in voluntary associations are,
next to social trust, the other facet “of the same underlying factor – social capital” (Putnam
1995a: 73). A positive correlation between these two elements seems plausible: “generalised
trust makes people more willing to take part in their communities and to endorse moral
commitments” (Uslaner 1999: 123). Initially, this relationship was hypothesised to be mutual,
but more recent research has stressed that “the connection is stronger from participation to
interpersonal trust, rather than the reverse” (Brehm and Rahn 1997: 999, see also Newton
1999b, Putnam 1995b: 666). Moreover, social trust is also considered to be responsible for
generating various forms of participation in politics, such as discussing politics, voting,
supporting a political party or a candidate etc. “In short, people who trust others are all-round
good citizens” (Putnam 2000: 137).
3
Following the initial recognition of social trust as a prerequisite for the efficiency of
political institutions and liveliness of citizens’ political engagement, it has also been proclaimed
as a “missing link” in economic development (Fine and Green 2000). The importance of trust
for the emergence of “ethical habits and reciprocal moral obligations” (Fukuyama 1995: 9),
decisive for functioning of industrial structure, has resulted in the identification of social capital
as a - hypothesised, but not yet fully evaluated - positive influence on economic productivity.
Thus, researchers focusing on the link between social capital and democracy supplemented their
analytical framework with economic indicators. Their conclusions seem unanimous: “where
trust and social networks flourish, individuals, firms, neighbours, and even nations prosper”
(Putnam 2000: 319, see also Inglehart 1990, 1999).
Such benevolent effects of social capital imply that its level is likely to be particularly
important for the future of countries undergoing the ‘dual transition’ from non-democratic, nonmarket regimes to market democracy in East-Central Europe. Levels of social capital may be
expected to be crucial for the success of consolidation in democratic and market institutions and
civic attitudes in the post-communist countries (c.f. Boix and Posner 1998, Inglehart 1997,
1999, Newton 1999b, Putnam 1993, 1995a, 1995b, 2000). Moreover, theorists of social capital,
apart from putting forward claims about the link between trust and networks, and the
development of liberal democracy, join the laments about the weakness of social networks and
potentially disadvantageous levels of distrust in post-communist societies. The theory of social
capital assumes that trust and social interconnectedness are the components of a democratic
political culture, thus low levels of social trust seem to be an inevitable heritage of the 50 years
Communist rule1 (Inglehart 1999, Rose 1994). In this paper, we examine these assumptions in
the light of extensive cross-national survey-based evidence that address questions of the
significance of levels of interpersonal trust in the region more thoroughly than has hitherto been
the case.
Data and methods of inquiry
The data used in this paper come from a survey conducted in 11 ECE countries in the
midst of transformation, 1993-1994. They give a unique opportunity to test the role social
capital plays in generating the emergence of political activism and positive responses to political
1
Uslaner summarises concisely why the level of social trust in a society and the openness of its political
system are expected to be co-dependent: “only in democracies is trust a rational gamble. When the heavy
hand of the state looms over society, it makes little sense to put too much faith in most other people … In
totalitarian societies, it makes little sense to trust anyone but your family and your closest friends. In
authoritarian societies, you might trust a somewhat larger circle. But only in democracies – and not even
all of them – will you give trust to strangers” (Uslaner 1999: 141).
4
and economic transformation at both the individual and aggregate levels. Assessment of both
individual and country-level evidence is especially valuable in this context, as the aggregatelevel analysis favoured by many authors offers apparently impressive evidence for the powerful
effects of social capital, but is unable to examine individual-level mechanisms that might
account for such ‘effects’.
Our analysis uses survey-based indices, as we are more interested in the relation
between social trust and other attitudes, such as perceptions of politics and economic
developments, than in the hypothesised influence of trust on official estimates of economic
growth, voting turnout etc. The main focus of our analysis is on respondents’ evaluation of
political and economic developments rather than on normative attitudes towards democracy and
market economy. First, we introduce the measures of the main concepts examined in the
analysis, while in the following section we examine the associations between these measures
implied by social capital theory. This involves investigating the relationship between the stocks
of social trust and various aspects of political and economic transformation in East-Central
Europe at the aggregate level. Then, we treat trust as an individual-level resource and use it as
an independent variable in several regression models explaining responses to political and
economic transformation. Later, we merge these two pictures using multi-level models that
allow us to account for the contextual effects while analysing individual-level data. As our
findings diverge from expectations derived from social capital theory, in the final section of the
paper we offer an alternative interpretation of the relationship between social trust and the
quality of institutional arrangements.
Indicators
The first indicator refers to the concept of social trust. Social trust is one of the
components of social capital and is most often defined as norms of generalised reciprocity and
trust, learned from participation in networks of civic engagement (Putnam 1993, 2000, Uslaner
1999, Inglehart 1990). In survey-based research social trust is usually measured by one simple
agree/disagree survey question about “trust in others” (Putnam 1993, 1995b, Inglehart 1997,
1999, Dekker et al. 1997, Torcal and Montero 1997, Stolle and Rochon 1997, Rose 1998, 1999,
Rose et al. 1997, Mishler and Rose 1998). In a few cases this measure has been further
developed to include faith in other people’s honesty and helpfulness (Brehm and Rahn 1997,
Paxton 1999, Putnam 2000), although still measured in terms of ‘agree/disagree’ items.
However, one question does not seem to be a sufficient measure of a multifaceted attitude, such
as “a set of institutionalised expectations that other social actors will reciprocate co-operative
overtures” (Boix and Posner 1998: 686). Single item measures have been criticised for their
limitations in capturing multifaceted topics, such as values or beliefs (e.g. Evans et al. 1996,
Heath et al. 1994). Therefore, to maximise the reliability of our measure of social trust and to
5
reduce the influence of random errors we selected five items that express individuals’ beliefs
about trust and norms of reciprocity2. Using a wider range of indicators is also necessary to
more adequately capture developments in the social capital theory: the initial stress on trust in
others has been moved to norms of reciprocity, as they imply interactions which are crucial for
the quality of social life (Putnam 2000). Therefore, we used the following five items to
construct the scale:
a) It is human nature to cooperate with other people.
b) Most people can be trusted.
c) If someone is in serious trouble, no one else cares about it.
d) If you are not always on your guard other people will take advantage of you.
e) A person cooperates with other people only when he or she sees it in his or her own interest.
All of these items have an agree-disagree format. Respondents almost unanimously
agree or strongly agree with the statement about human nature being cooperative. Moreover,
although only around 50% of respondents declare that they trust other people, this figure closely
resembles the reported results for the most ‘civic’ nations – Great Britain and the United States
(Hall 1999, Putnam 1995a, 1995b, Inglehart 1999, Newton 1999a). In the case of the remaining
three items, however, ‘negative’ (i.e. ‘strongly agree’ and ‘agree’) answers outweigh the ones
expressing trust and faith in cooperation. Thus, although 42% of respondents would expect help
and support from other people, almost 80% are afraid that others may take advantage of them,
and over 70% do not believe in unselfish cooperation. Whether or not these results can be
considered ‘negative’ or ‘positive’ in tone is difficult to assess, but their most important feature
is that they provide us with a range of responses across items that differ in terms of their general
levels of agreement and disagreement and thus allow the construction of normally distributed
multiple-indicator measure of the concept of social trust.
The second indicator we use is an index of political satisfaction. Although political
and economic performance can be measured by means of ‘objective’ indicators, such as
Freedom House rankings and per capita GNP, we use measures taken from our surveys that
more directly index citizens’ experiences of transition3. Seven items have been selected to
measure respondents’ opinions about these aspects of the workings of the political system in
2
For the details of the response distribution and construction of all the scales used in this paper, see
Appendix B.
3
For a critical evaluation of the validity of Freedom House rankings as a measure of the quality of
democracy, see Bollen (1993). Evans and Whitefield (1995) provide a critique of official measures of
economic experience in Eastern Europe. The advantages of survey-based indicators over ‘objective’
measures for examining the link between mass civic attitudes and political system quality has been argued
convincingly by Jackman and Miller (1998: 645).
6
their country.4 All of them are 5-point agree-disagree scales (see Appendix B for details). The
seven items refer to the implementation of democracy, general appraisals of the government’s
actions and respondents’ sense of political efficacy. Only slightly above 20% of respondents
evaluate the way democracy is being implemented in their countries positively, while 46% hold
a negative opinion. Two of three items referring to the government create a more optimistic
picture: 34% think that the majority of the society benefits from the government’s actions and
46% believe in the government’s effectiveness. However, as much as 56% of respondents
disagree with the statement that the government’s actions reflect ‘the popular will’. Moreover,
the three items referring to respondents’ political efficacy indicate their sense of ‘political
powerlessness’. As many as 65% of the respondents do not believe in the most basic feature of
democratic system - that citizens can influence the election of the government - while 72% think
they cannot influence government’s actions and 73% agree that officials are not concerned
about ‘ordinary’ people’s opinion. In general, these figures indicate that citizens in the new ECE
democracies had a negative opinion of their political systems in the mid-1990s. This applies not
only to feelings of efficacy, but also to the democratic functioning of their political systems.
As mentioned above, however, there is one more element involved in the ‘social
capital puzzle’: economic performance. To test the predictive power of the social capital
concept thoroughly we also examine the relationship between social trust and a measure of
satisfaction with economic performance. Again, five 5-point agree-disagree items are chosen as
indicators of satisfaction/disaffection with economic transformation in East-Central European
countries: they refer to the evaluation of market economy as well as observed and anticipated
change in the economic circumstances on individual and national level. Less then 30% of
respondents replied ‘positively’, i.e. expressing satisfaction or positive opinion about any of the
five aspects of the economic situation. In the case of questions about experience of micro- and
macro-level changes of economic circumstances, 66% and 76%, respectively, reported
experiencing a fall of living standards. At the same time, 45% respondents were not expecting
any future change in their economic situation and 43% did not predict such change at the
country level. Overall, evaluations of economic situation and living standards in ECE in the
mid-1990s were predictably rather low.
4
Some of these items are derived from the established tradition of survey research into the concept of
political efficacy originating in Campbell, Gurin and Miller's (1954) study. The concept and its related
indicators have usually been employed as part of the political culture approach to comparative analysis, as
in Almond and Verba (1963) and Barnes, Kaase, et al. (1979), but it is clearly also interpretable within a
rational choice framework concerned with the perceived pay-offs of democratic systems (Evans and
Whitefield 1995). Here, we do not have to make a choice about the ‘cultural’ or ‘rational’ status of
answers to these questions.
7
Table 1 below presents the average scores of particular countries. Countries are ranked
on the basis of their score on the social trust index: this allows us to observe whether the pattern
of distribution of social trust among countries is likely to be explained by any of the
characteristics invoked by social capital theorists (such as the stage of democratisation,
economic advancement, or cultural characteristics).
Table 1. about here.
As the table shows, in terms of stocks of social trust, three clusters of countries are
visible; Hungary, Czech Republic and Slovak Republic have average social trust scores of 2.76 2.78, while Bulgaria, Lithuania and Poland have scores lying between 2.89 and 2.91, and a third
looser cluster of Ukraine, Russia, Belarus and Estonia scores between 3.07 and 3.18. While the
first cluster seems intuitively predictable based on the countries’ central European geographical
location and economic characteristics, the second one is much more diverse in character. Even
more counterintuitive is the fact that Ukraine, Russia and Belarus have social trust scores higher
than those of any of the countries that are further advanced in the transition towards market
democracy. It is also interesting that Romania, despite its high levels of support for democracy
and the free market at that time (c.f. Evans and Whitefield 1995), has clearly the lowest score on
the index of social trust. In general, with the exception of Romania and Estonia, countries with
superior institutional performance seem to have systematically lower social trust scores5.
Table 1 shows also that the governmental evaluation index scores are low (i.e.
significantly below 3) across all countries. Country scores do not vary greatly, but there are
substantial and statistically significant differences between the highest scorers (the Czech
Republic and Romania) and the lowest (Ukraine and Russia). Levels of economic evaluation are
also low: no country’s average score reaches the mid-point of the scale, i.e. 3. The general
pattern of economic satisfaction scores is similar to what would be expected on the basis of
more ‘objective’ measures of economic development, e.g. more economically ‘advanced’
countries tend to score higher than less advanced countries.
Explaining responses to political and economic transformation: social trust
We have seen that East-Central Europeans’ levels of social trust appear to be
reasonably high and we find little evidence of the supposedly strong link between trust and
several features of the emerging liberal democracies in the region. In this section we elaborate
5
‘Institutional performance’ refers to political as well as economic performance; these can be estimated
on the basis of the Freedom House Survey (Freedom in the World Ratings) and OECD and EBRD
reports.
8
on these initial observations by exploring in more detail the aggregate level relationship
between social trust on one hand, and political, economic satisfaction and political participation
on the other. After that we examine the data at the individual-level and test whether social trust
is a resource that is important for the emergence of political activism and positive responses to
political and economic transformation.
Figures 1 and 2 below are graphic representations of the information contained in
Table 1. As social trust is supposed to be one of the main influences on satisfaction with
institutional performance and political engagement, it is shown in both graphs. Of course, when
plotting the scores on the two indices described above against scores on the social trust index we
expected a positive pattern: countries with higher stocks of social trust, such as Estonia or
Belarus, should have citizens whose evaluation of the political and economic transformation is
positive. However, in both cases the relationship is negative. It is most visible in the case of
social trust and political satisfaction: the pattern is very clear and relatively strong: citizens in
the countries with higher levels of social trust, such as Estonia, Belarus, Russia or Ukraine,
evaluate their political systems particularly poorly, while Romania and the Czech Republic, who
have the lowest scores on the social trust index, are comprised of rather satisfied and content
citizens. The relationship between stocks of social trust and economic satisfaction is much less
clear-cut. However, if Estonia and Romania, who constitute, respectively, the top and bottom
borderline cases in terms of social trust scores, were removed, the remaining countries would
form a very clear pattern again: the citizens of Ukraine, Belarus and Russia, despite their high
levels of social trust, are the most disillusioned with the economic situation in their countries,
while countries such as the Czech Republic, Lithuania or Hungary seem to score relatively high
on the economic satisfaction index, despite their rather low stocks of social trust.
Figures 1 and 2 about here.
The individual-level picture
Although social trust is usually treated as a property of communities, it is also a
resource of individuals: ‘stocks’ of social trust represent the aggregate of individual level
attitudes and behaviour. Thus we will now look at the role social trust plays in generating
positive responses to political and economic transformation at the individual level. Table 2
below presents the results of regressions of political and economic satisfaction on social trust.
As certain individual characteristics are supposed to be related to the levels of social trust, we
control for standard socio-economic characteristics, such as gender, age, education, job
situation, whether or not a respondent has children, income, their religious denomination and
their participation in religious services (c.f. Putnam 1995b, 2000, Brehm and Rahn 1997, Verba
et al. 1995, Torcal and Montero 1999). All models also control for country effects (the R2 refers
9
to models with all variables). However, as the focus of this paper is on the influence of social
capital on attitudes and behaviour related to the transformation, the coefficients of the socioeconomic characteristics and country dummy variables are not displayed here.
Table 2. about here.
Although the influence of trust on political and economic satisfaction, and political
participation is statistically significant in all cases, its coefficients are rather small in the latter
ones. Both models were estimated for a pooled sample that includes over 19000 respondents.
Obviously, such a large sample produces high levels of statistical significance for even very
weak associations. None the less, social trust seems to be substantively as well as statistically
significant for predicting political satisfaction. This is clear also when we look at the models
estimated for each country separately: social trust is highly significant for explaining levels of
political satisfaction in all countries; it is also important for explaining economic satisfaction in
eight out of eleven, though only in three of them is the effect relatively strong (i.e. beta > 0.1)
(see Tables B1 and B2 in the Appendix B).
Social trust, although positively correlated with both outcomes, is most important for
political satisfaction. Only in the models predicting the evaluation of politics can social trust not
be rivalled in magnitude by any socio-economic variable. In contrast, economic satisfaction is
much better explained by respondent’s income level, age (which has a negative effect) and
church service attendance.
The link between social trust and political and economic satisfaction: multilevel analysis
So far we have tested the influence of social trust on responses to political and
economic transformation separately at the aggregate and individual level. The results we
obtained are apparently contradictory, as the relationship between trust and the two types of
attitudes is different at each level of analysis. Therefore, it useful to merge these two levels and
test the individual level link between trust and responses to political and economic satisfaction
as well as simultaneously estimating the country differences. For this purpose we use multilevel
models (or ‘random coefficient models’) that are designed to analyse data with a hierarchical
structure (Bryk and Raudenbusch 1993). Neglecting this hierarchical structure would lead to an
underestimation of the standard errors of the coefficients, which might lead to the inference that
effects are significant when they are not (Woodhouse et al. 1996). Here we use a hierarchical
model in which the respondents are nested within the 11 countries in our sample.
The main difference between this type of model and the standard OLS model
controlling for the country effect by means of country dummy variables is that the multilevel
model estimates the significance of the higher level as a random effect rather than as a fixed
10
effect. It also allows for different slopes within countries, while the standard OLS model allows
only for different intercepts.
The model can be summarised by the following equation: yij = β0ijx0 + β 1jx1ij + β2x2j.
Subscript ij means that a given variable varies between respondents and countries, while
subscript j means that a variable varies only between countries and is constant for all
respondents within a given country. β0ij is an intercept explained by the formula β0ij = β0 + u0j +
e0ij, where u0j is a level 2 residual, that is the same for all respondents in a given country, while
e0ij is a level 1 residual, varying between persons and countries. uj and e0ij are assumed to be
uncorrelated. β 1j is explained by the formula β 1j = β 1j + u1j, where u1j is the slope residual.
The use of multilevel models enables us to estimate whether the general level of social
trust in a country influences political or economic satisfaction while controlling for the
individual level effects of trust within countries. We also estimate to what extent the countrylevel variance is explained by the differences in levels of trust between countries. In addition to
individual and country-level social trust, the model contains socio-economic characteristics, but
as only significant variables are included their number is reduced to four (gender, age, education
and income). Table 3 displays the unstandardised coefficients from both regressions, with
statistically significant coefficients in bold.
Table 3 about here.
Comparing Models 1 and 2 for both political and economic satisfaction we clearly see
that adding socio-economic background variables to the model does not significantly reduce the
strength of the influence of social trust on either dependent variable. They also confirm that the
influence of trust is much stronger in the case of political satisfaction than in the case of
economic satisfaction. Thus while social trust is among the strongest determinants of political
satisfaction, economic satisfaction is more strongly predicted by means of age, income and
education. More interestingly, however, it is clear that even when controlling for the range of
influences specified here, in the countries where citizens are more trusting they are also much
less satisfied with politics. This effect is very strong and highly statistically significant. In the
case of economic satisfaction the coefficient for social trust, despite being strong and – as in the
case of political satisfaction – negative, fails to attain the 0.05 significance level.
Conclusions
Our main objective has been to evaluate currently influential arguments about the role
of social trust as a positive influence on democratic functioning and economic performance in
post-communist countries. We have seen that levels of social trust in ECE are not particularly
low and yet citizens in this region seem relatively disillusioned with political and economic
11
transformation. We also have found that at the aggregate level in East-Central Europe social
trust is negatively correlated with political and economic satisfaction - although its effect is
significantly weaker in the case of economic satisfaction. In addition, when we included both
macro- and micro-level levels of observation in our analysis, we found that effect of trust on
political and economic satisfaction at the individual level is positive.
How then can we interpret these findings? Clearly, they cannot easily be understood
within the social capital framework advocated by Putnam (1993, 2000) or Inglehart (1997,
1999); the negative country-level relationship between social trust and political and economic
performance undermines claims linking trust with liberal democracy. However, the results can
be interpreted if we reverse the causal arrow, pointing from political or economic performance
towards social trust. Following Jackman and Miller (1998), we suggest that social trust should
itself be endogenised. Thus according to earlier theories of social capital - the best example is
probably James Coleman’s (1990) Foundations of Social Theory - trust is a result of an
institutional setting, not its source. It is more important as a resource in the absence of formal
rules and rule-makers accountability, such as has been the case under the communist rule, than
in highly predictable and regulated liberal democratic systems. Therefore, it plausibly results
from the process of individuals’ adaptation to the institutional setting rather than determining
their adaptation ability and adjustment strategies.
This interpretation also makes sense of our finding that, contrary to claims that social
trust can be generated only in a democratic context, there are reasonably high levels of
interpersonal trust in post-communist countries. There is no basis for assuming that trust was
absent under the previous communist regime in the region: distrust of state structures should not
be mistaken for distrust of fellow citizens. Quite the contrary, cooperation, reciprocity and trust
in others were resources necessary for survival in situations of economic scarcity and political
arbitrariness. As Gibson puts it: “perhaps in response to the totalitarianism of the past, Russians
have developed extensive social networks with high levels of political capacity” (Gibson 2001:
51). Although much research focuses on the role of blat networks and informal exchange in
political and economic system of Russia (e.g., Ledeneva 1998), the Russian experience can be
extended to other post-communist countries as well. Dependence on the spoken word and
informal connections is particularly strong in the context of institutional uncertainty and
unpredictability: it is also likely to result in the emergence of strong norms of interactions and
reciprocity (Coleman 1990). The negative correlation between national levels of political or
economic satisfaction and social trust are quite consistent with these claims; in countries where
citizens positively evaluate the workings of democracy and the market and perceive themselves
as influential, they have less need to rely on networks of informal relations with others than do
citizens who live in countries where the state and market institutions are largely inefficient.
12
When the political and economic systems respond to citizens’ needs, trust is less important for
political satisfaction.
In summary, social trust does not appear to be necessary for political and economic
success in East-Central Europe: it is not a major source of positive responses to the
transformation in this region. However, it may well be a result – or a symptom - of the
stabilisation and consolidation of the political and economic situation in the region. If social
trust is endogenised instead of being treated as a persistent cultural characteristic, the concept of
social capital is capable of encompassing various mechanisms responsible for generating trust,
which are specific for different institutional contexts. The findings presented in this paper do not
disprove the relevance of social trust for understanding popular support for a political and
economic system, but they show that it is necessary to specify more clearly the mechanisms at
work. They also indicate that to do so it is necessary to go beyond the assumptions developed in
models applied to Western liberal democratic contexts.
13
Appendix A: The Surveys
The surveys used in this paper were undertaken in 1993-94 as part of a British ESRC
funded research programme on Eastern Europe.6 A significant feature of this project is the
emphasis placed on the collection of high quality data. There was a strong emphasis on
maintaining consistently high standards of sampling across nations, preferably using national
probability samples, with carefully integrated questionnaire design, so that reliable and valid
estimates of population characteristics could be obtained. The studies in each country were
undertaken by researchers based usually at the respective academies of science employing
established teams of interviewers and coders. The surveys were designed in and coordinated
from Britain, but with important contributions from collaborators in many of the countries
studied.
The surveys are intended to be national, representative random samples. In most
countries respondents were obtained via computer generated random numbers taken from
electoral registers or censuses. They were then contacted by letter, prior to being interviewed
face-to-face in their own homes. Sometimes a random route method was also adopted. Thus the
surveys reported here differ from much other work in both Eastern and Western Europe in that
they do not rely to any great degree on quota samples of the sort gathered by opinion pollsters.
The research here relies mainly on probability samples. Even such probability samples, or
samples that come near to attaining those standards, have their limitations, especially if large
numbers of respondents refuse interviews thus jeopardising the representativeness of the
sample. However, in these surveys, and in those undertaken by other research teams in the
region, it has commonly been found that as many as 90% of people contacted agree to have an
interview in their homes.
Inevitably, sampling frames and stratification procedures varied between countries: in
some countries census information was considered more reliable; in others electoral records
were preferred; in other random route procedures were adopted with a Kish grid being used for
final respondent selection. The sampling frame used in most countries was the Electoral
Register, although in some cases it was thought better to use the Census, as some groups of the
population were likely to be under-represented among the electorate. The sampling methods
used involved several stages of selection. Typically, these took the form of: parliamentary
constituencies stratified by standard regions, population density and percentage owneroccupation, and selected systematically with probability proportionate to the size of the
electorate; polling districts; addresses chosen with probability proportionate to their number of
6
“Emerging forms of political representation and participation in Eastern Europe”, part of stage II of the
ESRC's East-West Programme.
14
listed electors; individuals - one at each address (or household) chosen by a random selection
procedure.
Table A.1 summarizes the main characteristics of the surveys. Each of the strategies
reported in Table A.1 was considered to be the most effective approach within the countries in
which it was adopted. As far as can be told, given the fallibilities of official data, non-response
biases are predictably like those in the West. Compared to Census data non-respondents tend to
be older and to have lower levels of education (see below for an example). Non-response
resulted mainly from non-contacts and refusals.
Table A1 about here.
The items in the questionnaires were developed over several months with extensive
back-translation and cross-translation procedures, which were facilitated by collective meetings
in Britain and smaller meetings in many of the post-communist countries studied. Items were
pilot tested on 50-100 respondents in each country prior to being finalized for use in the main
surveys. All interviews were conducted face-to-face in the respondents' homes. Interviewers
were usually experienced and were also given special training for some of the more difficult
aspects of the interview schedule relating to occupational classification. Checks on the
interviewers were carried out by local area supervisors. Quality was also checked in many
countries using follow-up studies of approximately 10% of the respondents' to the initial survey,
who were randomly selected and re-interviewed a few weeks later.
15
Appendix B: Construction of indices and country level analysis
Index of social trust
All of used items have an ‘agree-disagree’ format with five-point response scales. For
items a) and b) ‘strongly disagree’ is coded 1 and ‘strongly agree’ 5, while for c), d) and e) the
coding is reversed. ‘Don’t know’ responses are recoded to the mid-point. Factor analysis
detected two main dimensions (a), b) as one positively-worded dimension, and the remaining
three as a second, negatively worded dimension) and the reliability test for the 5 items indicated
that Cronbach’s alpha is a rather low 0.54. Nevertheless, to balance the scale and avoid an
acquiescence bias all five items were used to create an index of social trust (for a balanced scale
of this sort, an alpha of 0.54 is not unusual; see Heath, Evans and Martin 1994 and Evans and
Heath 1995 for discussions of this issue in scale construction). Figure B1 below presents
distribution of responses to each item
Figure B1 about here.
Index of political satisfaction
All variables were recoded into 5 point items, with answers ‘don’t know’ and ‘neithernor’ aggregated into the middle point of the scale. In the cases of A1b, B1e, B1h, F1g answers
were coded as ‘very negatively/strongly disagree’ = 1, ‘negatively/disagree’ = 2 etc., while in
the cases of F1b, F1e and F1i the direction was reversed, i.e. ‘strongly agree’ = 1, ‘agree’ = 2,
etc.
Although factor analysis detected two dimensions (F1b and F1e form separate factor
reflecting their difference from the other items in direction of question-wording), Cronbach’s
alpha for the 7 items is an acceptable 0.61. Again, as in the case of index of social trust, to
balance the scale all 7 items were used. Figure B2 presents the distribution of responses to each
question.7
Figure B2 about here.
Index of economic satisfaction
All items were recoded so as to form a five-point scale; ‘very negatively/fall a great
deal’ = 1, ‘negatively/fall a little’ = 2 etc., while ‘don’t know’ and ‘stay about the same’ (in the
7
In the case of item A1b, the labels ‘strongly agree’, ‘agree’, ‘disagree’ and ‘strongly disagree’ refer to
‘very positively’, ‘positively’, ‘negatively’ and ‘very negatively’.
16
case of item A2b: ‘don’t know/neither nor’) answers were recoded as the middle of the scale.
Factor analysis detects only one dimension and the Cronbach’s alpha for these 5 items is
relatively high: 0.71. Figure B3 presents the distribution of answers to each question8.
Figure B3 about here.
Table B1 about here.
Table B2 about here.
8
In the case of item A2b, the labels ‘great fall’, ‘little fall’, ‘a little rise’ and ‘significant rise’ refer
respectively to ‘very negatively’, ‘negatively’, ‘’positively’ and ‘very positively’.
17
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20
Table 1. Social trust, political satisfaction and economic satisfaction: average scores
Estonia
Belarus
Russia
Ukraine
Poland
Lithuania
Bulgaria
Slovak Rep.
Czech Rep.
Hungary
Romania
Social trust
(from 1 to 5)
3.180
3.157
3.108
3.069
2.905
2.896
2.886
2.775
2.769
2.764
2.655
Political satisfaction Economic satisfaction
(from 1 to 5)
(from 1 to 5)
2.472
2.655
2.413
2.267
2.335
2.340
2.296
2.040
2.565
2.640
2.616
2.451
2.727
2.398
2.551
2.382
2.876
3.030
2.677
2.440
2.828
2.547
21
Figure 1. Social trust and political satisfaction
Eston ia
Belarus
3.2
Russia
Ind ex of so cial tru st
3.1
Ukraine
3.0
P oland
Lithua nia
2.9
2.8
Slova k R.
Bulgaria
Czech R.
Hung ary
2.7
Rom an ia
2.6
2.2
2.3
2.4
2.5
2.6
2.7
2.8
2.9
Ind ex of political satisfac tion
Figure 2. Social trust and economic satisfaction
3.2
Estonia
B elarus
R ussia
Index of social trust
3.1Ukraine
3.0
Lithuania
B ulgaria
2.9
2.8
Po land
Slov ak R .
Hungary
2.7
C zech R .
R oman ia
2.6
2.0
2.2
2.4
2.6
2.8
3.0
3.2
Index of satisfaction with econo mic situatio n
22
Table 2. Regression of political satisfaction and economic satisfaction on social trust and
socio-economic characteristics (pooled sample, controlled for country effects)
Dependent variable:
(Constant)
Social trust
R2
Political satisfaction
B
Beta
Sig.
2.427
0.000
0.163 0.185
0.000
0.146
Economic satisfaction
B
Beta
Sig.
2.653
0.000
0.079 0.076 0.000
0.215
Table 3. Parameter estimates from a multilevel analysis of political satisfaction and
economic satisfaction, N1 (individual level) = 17.885, N2 (country level) = 11
Political satisfaction
Economic satisfaction
Model 1
Model 2
Model 3
Model 1
Model 2
Model 3
2.065 (0.048)
2.129 (0.052)
4.861 (0.535)
2.190 (0.073)
2.293 (0.075)
3.961 (1.122)
0.177 (0.018)
0.170 (0.017)
0.170 (0.017)
0.097 (0.019)
0.084 (0.015)
0.084 (0.015)
-0.056 (0.008)
-0.056 (0.008)
-0.013 (0.009)
-0.013 (0.009)
30 – 44
-0.054 (0.012)
-0.054 (0.012)
-0.175 (0.013)
-0.175 (0.013)
45 – 59
-0.072 (0.013)
-0.072 (0.013)
-0.321 (0.014)
-0.321 (0.014)
60 +
0.002 (0.014)
0.002 (0.014)
-0.281 (0.016)
-0.281 (0.016)
2
0.012 (0.014)
0.012 (0.014)
0.011 (0.016)
0.011 (0.016)
3
0.024 (0.015)
0.023 (0.015)
0.011 (0.017)
0.011 (0.017)
4
0.029 (0.015)
0.029 (0.015)
0.033 (0.017)
0.033 (0.017)
5
0.062 (0.016)
0.061 (0.016)
0.042 (0.017)
0.042 (0.017)
Average
0.045 (0.011)
0.045 (0.011)
0.099 (0.012)
0.099 (0.012)
Above average
0.124 (0.013)
0.124 (0.013)
0.386 (0.015)
0.386 (0.015)
Constant
Individual level characteristics
Social trust
Socio-economic characteristics
Gender (female)
Age group
18 – 29
Education level
1
Income
Below average
Country level characteristics
Stocks of social trust
-0.571 (0.383)
-0.935 (0.182)
Variance components
Country level
Constant
0.021 (0.011)
0.021 (0.011)
0.027 (0.013)
0.052 (0.025)
0.050 (0.024)
Social trust
0.003 (0.002)
0.003 (0.001)
0.003 (0.001)
0.003 (0.002)
0.002 (0.001)
0.002 (0.001)
Constant/social trust
-0.001 (0.003)
0.000 (0.003)
-0.007 (0.004)
-0.003 (0.005)
-0.001 (0.004)
-0.005 (0.004)
0.316 (0.003)
0.312 (0.003)
0.312 (0.003)
0.424 (0.004)
0.387 (0.004)
0.387 (0.004)
30246.30
30013.59
30005.08
35493.57
33865.45
33864.61
0.060 (0.028)
Individual level
Constant
-2*log(like)
23
Table A.1. Information on sampling and response rates for each survey
BULGARIA
SAMPLING FRAME
SAMPLING
RESPONSE RATE
adult pop (18+)
1992 census of households
names issued:
non-contact:
refused:
achieved:
Response rate:
names issued:
non-contact:
refused:
achieved:
adult pop (18+)
random route (rural)
Register Office address lists
(urban)
two-step cluster
1. 211 census districts (from
42000)
2.random:12 households from
each
1. 8 regions
2. 182 sampling points
(localities) from 13410
3. 2104 addresses, of which:
1681 random list sampling
(electoral register): 423 random
route + 111 quota
1. 5 regions
2. 15 counties
3. 321 sampling points
4.random-route/household
5.Kish matrix/respondent
1. 12 counties representing
regions
2. 78 sampling points
3. random selection of
individuals
1. 5 regions
2. 180 sampling points
3. rural - random route
urban - address list
adult pop (18+)
Central Register of Individuals
1. 8 regions
2. 4 types of settlements
adult pop (18+)
Electoral Records
1. 4 provinces
2. 4 types of settlements
3. electoral constituencies (126
from 51 settlements)
adult pop (18+)
lists of 'privatisation vouchers'
1. 10 regions
2. 56 settlements
3. indiv. from list of vouchers
adult pop (18+)
list of voters from 1992 in
sampled localities
1. 4 regions
2. 215 sampling points
(localities) from 4191
3. 2014 addresses of which:
1100 first wave; 914 second
wave.
Random list sampling (electoral
register) + 68 quota
1. 70 urban + 50 rural
settlements
2. 7 types (only urban) selection proportional to size of
pop. in each type
SUMMER
1993
CZECH
REPUBLIC
adult pop (18+)
list of voters from 1992 in
sampled localities
SPRING 1994
ESTONIA
adult pop (18+)
1989 census of households
SUMMER
1993
HUNGARY
SPRING 1994
LITHUANIA
SUMMER
1993
POLAND
adult pop (20+)
Central Register of Population
(1992)
SUMMER
1993
ROMANIA
SUMMER
1993
RUSSIA
SUMMER
1993
SLOVAKIA
SPRING 1994
UKRAINE
SUMMER
1993
adult pop (18+)
Housing Offices' residence list
of individuals
Response rate:
names issued:
non-contact:
refused:
achieved:
Response rate:
names issued:
non-contact:
refused:
achieved:
Response rate:
names issued:
non-contact:
refused:
achieved:
Response rate:
names issued:
non-contact:
refused:
achieved:
Response rate:
names issued:
non-contact:
refused:
achieved:
Response rate:
names issued:
non-contact:
refused:
achieved:
Response rate:
names issued:
non-contact:
refused:
achieved:
2532
517
83
1932
0.76
2104
404
291
1409+
111
0.67
Response rate:
2285
63
190
2029
0.89
1703
200
189
1314
0.77
2982
651
331
2000
0.67
2040
228
83
1729
0.85
2000
334
45
1621
0.81
2420
264
126
2030
0.84
2014
338
233
1443+
68
0.75
names issued:
non-contact:
refused:
achieved:
Response rate:
2984
220
227
2537
0.85
Response rate = achieved/names issued.
24
Figure B1. Indicators of social trust
100%
90%
80%
strongly agree
70%
agree
60%
neither nor
50%
disagree
40%
strongly disagree
30%
20%
10%
0%
B3a) It is human nature to B3b) Most people can be
cooperate with other
trusted
people
B3c) If someone is in
serious trouble, no one
else cares about it
B3d) If you are not
always on your guard
other people will take
advantage of you
B3e) A person cooperates
with other people only
when he or she sees it in
his or her own interest
Figure B2. Indicators of political satisfaction
100%
80%
strongly
disagree
60%
somewhat
disagree
neither-nor
40%
somewhat
agree
20%
strongly agree
0%
A1b) How would
B1e) The
B1h) Everyone
F1b) People like
F1e) Elected
F1g) On the
F1i) There is no
you evaluate the government acts has an influence me have no say in officials don’t care
whole, what
point in voting
actual practice of for the benefit of on the election of
what the
much what people governments do in
because the
democracy
the majority of the the government government does
like me think
this country
government can’t
society
reflects the wishes
make any
of ordinary people
difference
25
Figure B3. Indicators of economic evaluations
100%
80%
Great fall
Little fall
60%
Neither nor
40%
A little rise
Significant
rise
20%
0%
A2b) Evaluation of
market economy
L6d) Household
living standard
compared with the
past
L6e) Household
future living
standard
L7a) Country living L7b) Country future
standard compared
living standard
with the past
26
Table B1. Regression of the index of political satisfaction on social trust and socio-economic characteristics
Constant
Index of social trust
Sex (female)
Age
Level of education
1
2
3
4
5
Children (yes/no)
Job situation
In paid work
Student
Unemployed
Disabled
Retired
Housewife
Income level
Below average
Average
Above average
Denomination
Atheist
Protestant
Orthodox
Catholic
Church service attendance
R2
a
p < 0.001
b
p < 0.01
c
Belarus
B
Beta
2.116a
0.078 b 0.098
-0.043 -0.042
0.000 0.010
Bulgaria
B
Beta
2.101 a
0.134 a 0.184
0.048 c 0.050
0.002 0.067
0.013
0.083
0.043
0.051
0.025
-0.002
-0.003
0.012
0.011
-0.007
0.009
0.057
0.036
0.046
0.022
Czech Rep.
Estonia
B
Beta
B
Beta
1.879 a
2.404 a
0.283 a 0.238 0.121 a 0.143
-0.019 -0.014 -0.136 a -0.118
-0.001 -0.020 -0.004 b -0.114
-0.002 0.147 b 0.103 0.068 0.045
-0.002 0.256 a 0.159 -0.046 -0.032
0.011 0.265 a 0.118 -0.086 c -0.058
0.009 0.386 a 0.164 0.045 0.031
-0.007 -0.030 -0.021 -0.009 -0.008
0.031 0.012 0.091 0.027 0.237 c 0.076
0.021 0.007 -0.077 c -0.051 -0.107 -0.022
-0.078 -0.016 0.087 0.022 0.048 0.012
-0.005 -0.003 0.011 0.011 0.007 0.004
0.092 0.025 -0.118 -0.039 0.066 0.018
0.126
-0.055
0.073
0.027
0.056
Hungary
Lithuania
Poland
Romania
Russia
Slovak Rep.
Ukraine
B
Beta
B
Beta
B
Beta
B
Beta
B
Beta
B
Beta
B
Beta
2.210 a
2.257 a
1.721 a
2.033 a
1.956 a
1.908 a
1.888 a
0.192 a 0.211 0.138 a 0.171 0.148 a 0.183 0.208 a 0.218 0.183 a 0.211 0.200 a 0.207 0.152 a 0.187
0.004 0.004 -0.069 b -0.063 -0.101 b -0.089 -0.057 -0.049 -0.114 a -0.096 -0.069 c -0.058 -0.082 a -0.073
-0.002 -0.060 -0.001 -0.037 -0.003 c -0.080 0.003 0.071 -0.002 -0.057 0.000 0.005 0.002 0.051
-0.102
-0.042
-0.037
0.162 c
-0.040
-0.070
-0.033
-0.016
0.079
-0.031
0.007
0.036
0.008
0.080
-0.016
0.004 -0.083 -0.071 0.057
0.032 -0.162 c -0.124 0.126
0.006 -0.082 -0.056 0.184 a
0.055 -0.100 -0.056 0.116
-0.015 -0.059 -0.051 0.010
0.038 0.224 0.046
-0.023 -0.126 c -0.059
0.017 -0.104 -0.042
0.020 0.048 0.034
0.024 -0.193 -0.055
0.100
-0.012
-0.149
0.116 c
-0.005
0.040
-0.005
-0.039
0.087
-0.002
0.116
-0.048
-0.020
0.017
0.038
0.063
-0.024
-0.007
0.012
0.018
0.039
0.083
0.151
0.077
0.008
0.059
-0.003
0.009
0.071
-0.056
0.038
-0.002
0.006
0.053
-0.044
-0.033
0.072
0.097
0.166 b
0.002
-0.026 -0.007 -0.005
0.054 -0.014 -0.008
0.052 0.026 0.019
0.090 0.028 0.021
0.002 -0.054 c -0.048
-0.092 -0.022 0.059 0.020
-0.072 -0.025 -0.276 b -0.077
-0.043 -0.010 0.224 0.040
0.050 0.035 -0.008 -0.005
-0.077 -0.027 0.083 0.026
0.077
-0.059
0.080
0.001
0.016
0.023
-0.027
0.025
0.001
0.005
0.091
-0.016
0.009
-0.011
0.103
0.030
-0.005
0.002
-0.009
0.036
0.034 0.032 0.042 0.044 0.032 0.023 0.067 0.056 0.033 0.026 0.093 b 0.084 0.065 0.055 0.023 0.020 0.054 0.045 0.033 0.028 -0.015 -0.013
0.050 0.032 0.072 0.053 0.191 b 0.106 0.150 b 0.094 0.024 0.016 0.121 b 0.101 0.087 0.056 0.085 0.064 0.284 a 0.214 0.101 0.067 -0.014 -0.010
0.003 0.000
-0.014 -0.013
-0.001 0.000
0.011 0.035
0.024
0.492 c
0.109 b
-0.160
-0.016
0.059 0.244 c 0.065 -0.025 -0.016 -0.011 -0.006 -0.105 -0.015
0.109
-0.358 a -0.233
0.041 0.015 0.522 b
-0.031 -0.068 -0.047 -0.274 -0.042 -0.043 -0.034 0.035 0.028 0.429 b
-0.062 0.048 b 0.122 0.054 a 0.168 0.040 b 0.133 -0.012 -0.043 0.064 a
0.061
0.140
0.109
0.099
0.053
-0.163 -0.040
0.063 0.033
0.132 0.059 0.039 -0.044 -0.037
-0.020 -0.018
0.182 0.049 0.027
0.092 0.070
0.154 -0.002 -0.006 0.005 0.014 0.008 0.030 0.018 c 0.068
0.097
0.083
0.126
0.088
0.049
p < 0.05
27
Table B2. Regression of the index of economic satisfaction on social trust and socio-economic characteristics
Constant
Index of social trust
Sex (female)
Age
Level of education
1
2
3
4
5
Children (yes/no)
Job situation
In paid work
Student
Unemployed
Disabled
Retired
Housewife
Income level
Below average
Average
Above average
Denomination
Atheist
Protestant
Orthodox
Catholic
Church service attendance
R2
a
p < 0.001
b
p < 0.01
c
Belarus
Bulgaria
Czech Rep.
Estonia
B
Beta
B
Beta
B
Beta
B
Beta
2.434a
2.282a
2.950a
3.248a
0.048 0.046 0.015 0.014 0.094b 0.077 0.045c 0.048
0.061 0.046 0.060 0.043 -0.005 -0.004 -0.174a -0.135
-0.013a -0.266 -0.005b -0.118 -0.007a -0.179 -0.014a -0.360
-0.021 -0.012 0.063c 0.041
-0.052 -0.028 0.130c 0.064
-0.056 -0.036 0.190b 0.121
-0.085 -0.059 0.152c 0.084
-0.038 -0.026 -0.083 c -0.060
-0.005 -0.003
0.162b 0.098
0.125 0.054
0.217b 0.090
0.000 0.000
-0.104 -0.031 0.046 0.010 0.099 0.031
0.182 0.051 -0.147b -0.069 -0.089 -0.017
-0.102 -0.016 0.140 0.024 -0.160 -0.039
0.177c 0.086 -0.068 -0.047 -0.086 -0.050
-0.025 -0.005 0.078 0.018 -0.081 -0.021
Hungary
B
Beta
2.377 a
0.122 a 0.130
-0.059 -0.045
-0.002 -0.059
0.081 0.047 -0.134 c -0.089
0.003 0.002 -0.002 -0.002
-0.088 -0.053 0.002 0.001
0.009 0.006 0.112 0.052
-0.024 -0.018 -0.126 b -0.096
Lithuania
B
Beta
2.500 a
0.060 a 0.083
-0.049 c -0.050
-0.006 a -0.190
-0.006 -0.004 -0.100 -0.072 0.012 0.006 -0.026 -0.014
-0.060 -0.059 -0.209 b -0.135 -0.140 -0.070 0.020 0.010
-0.048 -0.041 -0.117 -0.067 0.022 0.013 -0.054 -0.030
0.002 0.001 -0.014 -0.007 -0.025 -0.012 -0.030 -0.018
-0.034 -0.034 -0.118 b -0.086 0.026 0.016 -0.087 c -0.056
-0.001 0.000
0.086 0.061
0.142 c 0.071
0.196 b 0.101
-0.004 -0.003
-0.052 -0.037
-0.021 -0.011
-0.024 -0.017
-0.066 -0.048
-0.016 -0.014
0.214 b 0.096 0.190 0.034 0.040 0.011
-0.076 -0.032 -0.153 -0.039 0.027 0.006
-0.077 -0.023 -0.262 -0.046 -0.087 -0.013
0.011 0.007 0.122 0.065 -0.034 -0.018
0.138 c 0.054 0.051 0.013 0.084 0.021
-0.019 -0.005
-0.070 -0.030
-0.066 -0.020
0.029 0.018
-0.019 -0.006
-0.119 -0.038
-0.093 -0.026
-0.090 -0.020
-0.042 -0.033
0.004 0.001
-0.007 -0.002 0.159 0.032 -0.002 -0.001
-0.111 -0.040 -0.170 b -0.076 0.002 0.001
0.067 0.014 -0.230 b -0.088 -0.214 b -0.063
0.110c 0.071 -0.068 -0.047 0.024 0.020
0.163b 0.061 -0.189 -0.052 0.095 c 0.047
0.148b 0.107 0.152a 0.110 0.013 0.009 0.084b 0.063
0.490a 0.240 0.469a 0.242 0.433a 0.233 0.424a 0.237
Poland
Romania
Russia
Slovak Rep.
Ukraine
B
Beta
B
Beta
B
Beta
B
Beta
B
Beta
2.142 a
2.079 a
2.354 a
2.207 a
1.974 a
0.091 a 0.094 0.172 a 0.136 0.065 b 0.062 0.139 a 0.136 0.079 a 0.093
-0.055 -0.040 -0.059 -0.038 -0.012 -0.008 -0.045 -0.035 0.035 0.030
-0.007 a -0.157 -0.006 b -0.123 -0.009 a -0.169 -0.008 a -0.187 -0.006 a -0.185
0.020 0.015 0.017 0.017 0.222 a 0.158 0.034 0.022 0.174 a 0.119 0.015 0.012 0.039 0.033
0.097 0.063 0.252 a 0.235 0.455 a 0.249 0.237 a 0.133 0.586 a 0.365 0.255 a 0.160 0.194 a 0.128
-0.516 -0.032 0.440 0.037 0.033 0.009 0.037 0.020 -0.078 -0.045 0.043 0.007
0.085 0.016
-0.017 -0.009
-0.107 -0.077 -0.069 -0.048
-0.175b -0.101
-0.084 -0.035 0.368 0.078 0.059 0.030 -0.100 c -0.069
0.001 0.001
-0.142 -0.043 0.204 0.028 -0.084 -0.056 -0.415c -0.056 -0.163 b -0.124 0.055 0.050 0.361 c 0.129 -0.005 -0.002
0.030 0.021
0.044b 0.113 0.048a 0.131 0.048b 0.118 0.020 0.056 0.059 a 0.188 0.001 0.004 0.036 b 0.073 0.061 a 0.118 0.021 0.048 0.014 0.050 0.023 c 0.084
0.115
0.152
0.178
0.213
0.105
0.118
0.144
0.077
0.178
0.121
0.072
p < 0.05
28
Table 1. Social trust, political satisfaction and economic satisfaction: average scores
Estonia
Belarus
Russia
Ukraine
Poland
Lithuania
Bulgaria
Slovak Rep.
Czech Rep.
Hungary
Romania
Social trust
(from 1 to 5)
3.180
3.157
3.108
3.069
2.905
2.896
2.886
2.775
2.769
2.764
2.655
Political satisfaction Economic satisfaction
(from 1 to 5)
(from 1 to 5)
2.472
2.655
2.413
2.267
2.335
2.340
2.296
2.040
2.565
2.640
2.616
2.451
2.727
2.398
2.551
2.382
2.876
3.030
2.677
2.440
2.828
2.547
29
Figure 1. Social trust and political satisfaction
Eston ia
Belarus
3.2
Russia
Ind ex of so cial tru st
3.1
Ukraine
3.0
P oland
Lithua nia
2.9
2.8
Slova k R.
Bulgaria
Czech R.
Hung ary
2.7
Rom an ia
2.6
2.2
2.3
2.4
2.5
2.6
2.7
2.8
2.9
Ind ex of political satisfac tion
Figure 2. Social trust and economic satisfaction
3.2
Estonia
B elarus
R ussia
Index of social trust
3.1Ukraine
3.0
Lithuania
B ulgaria
2.9
2.8
Po land
Slov ak R .
Hungary
2.7
C zech R .
R oman ia
2.6
2.0
2.2
2.4
2.6
2.8
3.0
3.2
Index of satisfaction with econo mic situatio n
30
Table 2. Regression of political satisfaction and economic satisfaction on social trust and
socio-economic characteristics (pooled sample, controlled for country effects)
Dependent variable:
(Constant)
Social trust
R2
Political satisfaction
B
Beta
Sig.
2.427
0.000
0.163 0.185
0.000
0.146
Economic satisfaction
B
Beta
Sig.
2.653
0.000
0.079 0.076 0.000
0.215
Table 3. Parameter estimates from a multilevel analysis of political satisfaction and
economic satisfaction, N1 (individual level) = 17.885, N2 (country level) = 11
Political satisfaction
Economic satisfaction
Model 1
Model 2
Model 3
Model 1
Model 2
Model 3
2.065 (0.048)
2.129 (0.052)
4.861 (0.535)
2.190 (0.073)
2.293 (0.075)
3.961 (1.122)
0.177 (0.018)
0.170 (0.017)
0.170 (0.017)
0.097 (0.019)
0.084 (0.015)
0.084 (0.015)
-0.056 (0.008)
-0.056 (0.008)
-0.013 (0.009)
-0.013 (0.009)
30 – 44
-0.054 (0.012)
-0.054 (0.012)
-0.175 (0.013)
-0.175 (0.013)
45 – 59
-0.072 (0.013)
-0.072 (0.013)
-0.321 (0.014)
-0.321 (0.014)
60 +
0.002 (0.014)
0.002 (0.014)
-0.281 (0.016)
-0.281 (0.016)
2
0.012 (0.014)
0.012 (0.014)
0.011 (0.016)
0.011 (0.016)
3
0.024 (0.015)
0.023 (0.015)
0.011 (0.017)
0.011 (0.017)
4
0.029 (0.015)
0.029 (0.015)
0.033 (0.017)
0.033 (0.017)
5
0.062 (0.016)
0.061 (0.016)
0.042 (0.017)
0.042 (0.017)
Average
0.045 (0.011)
0.045 (0.011)
0.099 (0.012)
0.099 (0.012)
Above average
0.124 (0.013)
0.124 (0.013)
0.386 (0.015)
0.386 (0.015)
Constant
Individual level characteristics
Social trust
Socio-economic characteristics
Gender (female)
Age group
18 – 29
Education level
1
Income
Below average
Country level characteristics
Stocks of social trust
-0.571 (0.383)
-0.935 (0.182)
Variance components
Country level
Constant
0.021 (0.011)
0.021 (0.011)
0.027 (0.013)
0.052 (0.025)
0.050 (0.024)
Social trust
0.003 (0.002)
0.003 (0.001)
0.003 (0.001)
0.003 (0.002)
0.002 (0.001)
0.002 (0.001)
Constant/social trust
-0.001 (0.003)
0.000 (0.003)
-0.007 (0.004) -0.003 (0.005)
-0.001 (0.004)
-0.005 (0.004)
0.316 (0.003)
0.312 (0.003)
0.312 (0.003)
0.424 (0.004)
0.387 (0.004)
0.387 (0.004)
30246.30
30013.59
30005.08
35493.57
33865.45
33864.61
0.060 (0.028)
Individual level
Constant
-2*log(like)
31
Table A.1. Information on sampling and response rates for each survey
BULGARIA
SAMPLING FRAME
SAMPLING
RESPONSE RATE
adult pop (18+)
1992 census of households
names issued:
non-contact:
refused:
achieved:
Response rate:
names issued:
non-contact:
refused:
achieved:
adult pop (18+)
random route (rural)
Register Office address lists
(urban)
two-step cluster
1. 211 census districts (from
42000)
2.random:12 households from
each
1. 8 regions
2. 182 sampling points
(localities) from 13410
3. 2104 addresses, of which:
1681 random list sampling
(electoral register): 423 random
route + 111 quota
1. 5 regions
2. 15 counties
3. 321 sampling points
4.random-route/household
5.Kish matrix/respondent
1. 12 counties representing
regions
2. 78 sampling points
3. random selection of
individuals
1. 5 regions
2. 180 sampling points
3. rural - random route
urban - address list
adult pop (18+)
Central Register of Individuals
1. 8 regions
2. 4 types of settlements
adult pop (18+)
Electoral Records
1. 4 provinces
2. 4 types of settlements
3. electoral constituencies (126
from 51 settlements)
adult pop (18+)
lists of 'privatisation vouchers'
1. 10 regions
2. 56 settlements
3. indiv. from list of vouchers
adult pop (18+)
list of voters from 1992 in
sampled localities
1. 4 regions
2. 215 sampling points
(localities) from 4191
3. 2014 addresses of which:
1100 first wave; 914 second
wave.
Random list sampling (electoral
register) + 68 quota
1. 70 urban + 50 rural
settlements
2. 7 types (only urban) selection proportional to size of
pop. in each type
SUMMER
1993
CZECH
REPUBLIC
adult pop (18+)
list of voters from 1992 in
sampled localities
SPRING 1994
ESTONIA
adult pop (18+)
1989 census of households
SUMMER
1993
HUNGARY
SPRING 1994
LITHUANIA
SUMMER
1993
POLAND
adult pop (20+)
Central Register of Population
(1992)
SUMMER
1993
ROMANIA
SUMMER
1993
RUSSIA
SUMMER
1993
SLOVAKIA
SPRING 1994
UKRAINE
SUMMER
1993
adult pop (18+)
Housing Offices' residence list
of individuals
Response rate:
names issued:
non-contact:
refused:
achieved:
Response rate:
names issued:
non-contact:
refused:
achieved:
Response rate:
names issued:
non-contact:
refused:
achieved:
Response rate:
names issued:
non-contact:
refused:
achieved:
Response rate:
names issued:
non-contact:
refused:
achieved:
Response rate:
names issued:
non-contact:
refused:
achieved:
Response rate:
names issued:
non-contact:
refused:
achieved:
2532
517
83
1932
0.76
2104
404
291
1409+
111
0.67
Response rate:
2285
63
190
2029
0.89
1703
200
189
1314
0.77
2982
651
331
2000
0.67
2040
228
83
1729
0.85
2000
334
45
1621
0.81
2420
264
126
2030
0.84
2014
338
233
1443+
68
0.75
names issued:
non-contact:
refused:
achieved:
Response rate:
2984
220
227
2537
0.85
Response rate = achieved/names issued.
32
Figure B1. Indicators of social trust
100%
90%
80%
strongly agree
70%
agree
60%
neither nor
50%
disagree
40%
strongly disagree
30%
20%
10%
0%
B3a) It is human nature to B3b) Most people can be
cooperate with other
trusted
people
B3c) If someone is in
serious trouble, no one
else cares about it
B3d) If you are not
always on your guard
other people will take
advantage of you
B3e) A person cooperates
with other people only
when he or she sees it in
his or her own interest
Figure B2. Indicators of political satisfaction
100%
80%
strongly
disagree
60%
somewhat
disagree
neither-nor
40%
somewhat
agree
20%
strongly agree
0%
A1b) How would
B1e) The
B1h) Everyone
F1b) People like
F1e) Elected
F1g) On the
F1i) There is no
you evaluate the government acts has an influence me have no say in officials don’t care
whole, what
point in voting
actual practice of for the benefit of on the election of
what the
much what people governments do in
because the
democracy
the majority of the the government government does
like me think
this country
government can’t
society
reflects the wishes
make any
of ordinary people
difference
33
Figure B3. Indicators of economic evaluations
100%
80%
Great fall
Little fall
60%
Neither nor
40%
A little rise
Significant
rise
20%
0%
A2b) Evaluation of
market economy
L6d) Household
living standard
compared with the
past
L6e) Household
future living
standard
L7a) Country living L7b) Country future
standard compared
living standard
with the past
34
Table B1. Regression of the index of political satisfaction on social trust and socio-economic characteristics
Constant
Index of social trust
Sex (female)
Age
Level of education
1
2
3
4
5
Children (yes/no)
Job situation
In paid work
Student
Unemployed
Disabled
Retired
Housewife
Income level
Below average
Average
Above average
Denomination
Atheist
Protestant
Orthodox
Catholic
Church service attendance
R2
a
p < 0.001
b
p < 0.01
c
Belarus
B
Beta
2.116a
0.078 b 0.098
-0.043 -0.042
0.000 0.010
Bulgaria
B
Beta
2.101 a
0.134 a 0.184
0.048 c 0.050
0.002 0.067
0.013
0.083
0.043
0.051
0.025
-0.002
-0.003
0.012
0.011
-0.007
0.009
0.057
0.036
0.046
0.022
Czech Rep.
Estonia
B
Beta
B
Beta
1.879 a
2.404 a
0.283 a 0.238 0.121 a 0.143
-0.019 -0.014 -0.136 a -0.118
-0.001 -0.020 -0.004 b -0.114
-0.002 0.147 b 0.103 0.068 0.045
-0.002 0.256 a 0.159 -0.046 -0.032
0.011 0.265 a 0.118 -0.086 c -0.058
0.009 0.386 a 0.164 0.045 0.031
-0.007 -0.030 -0.021 -0.009 -0.008
0.031 0.012 0.091 0.027 0.237 c 0.076
0.021 0.007 -0.077 c -0.051 -0.107 -0.022
-0.078 -0.016 0.087 0.022 0.048 0.012
-0.005 -0.003 0.011 0.011 0.007 0.004
0.092 0.025 -0.118 -0.039 0.066 0.018
0.126
-0.055
0.073
0.027
0.056
Hungary
Lithuania
Poland
Romania
Russia
Slovak Rep.
Ukraine
B
Beta
B
Beta
B
Beta
B
Beta
B
Beta
B
Beta
B
Beta
2.210 a
2.257 a
1.721 a
2.033 a
1.956 a
1.908 a
1.888 a
0.192 a 0.211 0.138 a 0.171 0.148 a 0.183 0.208 a 0.218 0.183 a 0.211 0.200 a 0.207 0.152 a 0.187
0.004 0.004 -0.069 b -0.063 -0.101 b -0.089 -0.057 -0.049 -0.114 a -0.096 -0.069 c -0.058 -0.082 a -0.073
-0.002 -0.060 -0.001 -0.037 -0.003 c -0.080 0.003 0.071 -0.002 -0.057 0.000 0.005 0.002 0.051
-0.102
-0.042
-0.037
0.162 c
-0.040
-0.070
-0.033
-0.016
0.079
-0.031
0.007
0.036
0.008
0.080
-0.016
0.004 -0.083 -0.071 0.057
0.032 -0.162 c -0.124 0.126
0.006 -0.082 -0.056 0.184 a
0.055 -0.100 -0.056 0.116
-0.015 -0.059 -0.051 0.010
0.038 0.224 0.046
-0.023 -0.126 c -0.059
0.017 -0.104 -0.042
0.020 0.048 0.034
0.024 -0.193 -0.055
0.100
-0.012
-0.149
0.116 c
-0.005
0.040
-0.005
-0.039
0.087
-0.002
0.116
-0.048
-0.020
0.017
0.038
0.063
-0.024
-0.007
0.012
0.018
0.039
0.083
0.151
0.077
0.008
0.059
-0.003
0.009
0.071
-0.056
0.038
-0.002
0.006
0.053
-0.044
-0.033
0.072
0.097
0.166 b
0.002
-0.026 -0.007 -0.005
0.054 -0.014 -0.008
0.052 0.026 0.019
0.090 0.028 0.021
0.002 -0.054 c -0.048
-0.092 -0.022 0.059 0.020
-0.072 -0.025 -0.276 b -0.077
-0.043 -0.010 0.224 0.040
0.050 0.035 -0.008 -0.005
-0.077 -0.027 0.083 0.026
0.077
-0.059
0.080
0.001
0.016
0.023
-0.027
0.025
0.001
0.005
0.091
-0.016
0.009
-0.011
0.103
0.030
-0.005
0.002
-0.009
0.036
0.034 0.032 0.042 0.044 0.032 0.023 0.067 0.056 0.033 0.026 0.093 b 0.084 0.065 0.055 0.023 0.020 0.054 0.045 0.033 0.028 -0.015 -0.013
0.050 0.032 0.072 0.053 0.191 b 0.106 0.150 b 0.094 0.024 0.016 0.121 b 0.101 0.087 0.056 0.085 0.064 0.284 a 0.214 0.101 0.067 -0.014 -0.010
0.003 0.000
-0.014 -0.013
-0.001 0.000
0.011 0.035
0.024
0.492 c
0.109 b
-0.160
-0.016
0.059 0.244 c 0.065 -0.025 -0.016 -0.011 -0.006 -0.105 -0.015
0.109
-0.358 a -0.233
0.041 0.015 0.522 b
-0.031 -0.068 -0.047 -0.274 -0.042 -0.043 -0.034 0.035 0.028 0.429 b
-0.062 0.048 b 0.122 0.054 a 0.168 0.040 b 0.133 -0.012 -0.043 0.064 a
0.061
0.140
0.109
0.099
0.053
-0.163 -0.040
0.063 0.033
0.132 0.059 0.039 -0.044 -0.037
-0.020 -0.018
0.182 0.049 0.027
0.092 0.070
0.154 -0.002 -0.006 0.005 0.014 0.008 0.030 0.018 c 0.068
0.097
0.083
0.126
0.088
0.049
p < 0.05
35
Table B2. Regression of the index of economic satisfaction on social trust and socio-economic characteristics
Constant
Index of social trust
Sex (female)
Age
Level of education
1
2
3
4
5
Children (yes/no)
Job situation
In paid work
Student
Unemployed
Disabled
Retired
Housewife
Income level
Below average
Average
Above average
Denomination
Atheist
Protestant
Orthodox
Catholic
Church service attendance
R2
a
p < 0.001
b
p < 0.01
c
Belarus
Bulgaria
Czech Rep.
Estonia
B
Beta
B
Beta
B
Beta
B
Beta
2.434a
2.282a
2.950a
3.248a
0.048 0.046 0.015 0.014 0.094b 0.077 0.045c 0.048
0.061 0.046 0.060 0.043 -0.005 -0.004 -0.174a -0.135
-0.013a -0.266 -0.005b -0.118 -0.007a -0.179 -0.014a -0.360
-0.021 -0.012 0.063c 0.041
-0.052 -0.028 0.130c 0.064
-0.056 -0.036 0.190b 0.121
-0.085 -0.059 0.152c 0.084
-0.038 -0.026 -0.083 c -0.060
-0.005 -0.003
0.162b 0.098
0.125 0.054
0.217b 0.090
0.000 0.000
-0.104 -0.031 0.046 0.010 0.099 0.031
0.182 0.051 -0.147b -0.069 -0.089 -0.017
-0.102 -0.016 0.140 0.024 -0.160 -0.039
0.177c 0.086 -0.068 -0.047 -0.086 -0.050
-0.025 -0.005 0.078 0.018 -0.081 -0.021
Hungary
B
Beta
2.377 a
0.122 a 0.130
-0.059 -0.045
-0.002 -0.059
0.081 0.047 -0.134 c -0.089
0.003 0.002 -0.002 -0.002
-0.088 -0.053 0.002 0.001
0.009 0.006 0.112 0.052
-0.024 -0.018 -0.126 b -0.096
Lithuania
B
Beta
2.500 a
0.060 a 0.083
-0.049 c -0.050
-0.006 a -0.190
-0.006 -0.004 -0.100 -0.072 0.012 0.006 -0.026 -0.014
-0.060 -0.059 -0.209 b -0.135 -0.140 -0.070 0.020 0.010
-0.048 -0.041 -0.117 -0.067 0.022 0.013 -0.054 -0.030
0.002 0.001 -0.014 -0.007 -0.025 -0.012 -0.030 -0.018
-0.034 -0.034 -0.118 b -0.086 0.026 0.016 -0.087 c -0.056
-0.001 0.000
0.086 0.061
0.142 c 0.071
0.196 b 0.101
-0.004 -0.003
-0.052 -0.037
-0.021 -0.011
-0.024 -0.017
-0.066 -0.048
-0.016 -0.014
0.214 b 0.096 0.190 0.034 0.040 0.011
-0.076 -0.032 -0.153 -0.039 0.027 0.006
-0.077 -0.023 -0.262 -0.046 -0.087 -0.013
0.011 0.007 0.122 0.065 -0.034 -0.018
0.138 c 0.054 0.051 0.013 0.084 0.021
-0.019 -0.005
-0.070 -0.030
-0.066 -0.020
0.029 0.018
-0.019 -0.006
-0.119 -0.038
-0.093 -0.026
-0.090 -0.020
-0.042 -0.033
0.004 0.001
-0.007 -0.002 0.159 0.032 -0.002 -0.001
-0.111 -0.040 -0.170 b -0.076 0.002 0.001
0.067 0.014 -0.230 b -0.088 -0.214 b -0.063
0.110c 0.071 -0.068 -0.047 0.024 0.020
0.163b 0.061 -0.189 -0.052 0.095 c 0.047
0.148b 0.107 0.152a 0.110 0.013 0.009 0.084b 0.063
0.490a 0.240 0.469a 0.242 0.433a 0.233 0.424a 0.237
Poland
Romania
Russia
Slovak Rep.
Ukraine
B
Beta
B
Beta
B
Beta
B
Beta
B
Beta
2.142 a
2.079 a
2.354 a
2.207 a
1.974 a
0.091 a 0.094 0.172 a 0.136 0.065 b 0.062 0.139 a 0.136 0.079 a 0.093
-0.055 -0.040 -0.059 -0.038 -0.012 -0.008 -0.045 -0.035 0.035 0.030
-0.007 a -0.157 -0.006 b -0.123 -0.009 a -0.169 -0.008 a -0.187 -0.006 a -0.185
0.020 0.015 0.017 0.017 0.222 a 0.158 0.034 0.022 0.174 a 0.119 0.015 0.012 0.039 0.033
0.097 0.063 0.252 a 0.235 0.455 a 0.249 0.237 a 0.133 0.586 a 0.365 0.255 a 0.160 0.194 a 0.128
-0.516 -0.032 0.440 0.037 0.033 0.009 0.037 0.020 -0.078 -0.045 0.043 0.007
0.085 0.016
-0.017 -0.009
-0.107 -0.077 -0.069 -0.048
-0.175b -0.101
-0.084 -0.035 0.368 0.078 0.059 0.030 -0.100 c -0.069
0.001 0.001
-0.142 -0.043 0.204 0.028 -0.084 -0.056 -0.415c -0.056 -0.163 b -0.124 0.055 0.050 0.361 c 0.129 -0.005 -0.002
0.030 0.021
0.044b 0.113 0.048a 0.131 0.048b 0.118 0.020 0.056 0.059 a 0.188 0.001 0.004 0.036 b 0.073 0.061 a 0.118 0.021 0.048 0.014 0.050 0.023 c 0.084
0.115
0.152
0.178
0.213
0.105
0.118
0.144
0.077
0.178
0.121
0.072
p < 0.05
36
37