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Formation of social capital in Eastern
Europe: Explaining the gap vis-à-vis
developed countries
KLARITA
G
ERXHAN I
(University of Amsterdam)
Data: 25/06/2004 (Sexta-feira)
Horário: 12h 30min
Local:
Praia de Botafogo, 190 - 110 andar
Auditório nO 2 Coordenação:
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Formation of Social Capital in Eastern Europe:
Explaining the Gap vis-à-vis Developed Countries
v
Jan Fidrmuc * and Klarita Gerxhani**
April2004
Abstract
Recent Eurobarometer survey data are used to document and explain the leveI of
social capital in thirteen new members and fifteen current members of the European
Union. Social capital in Eastern Europe - measured by participation in clubs and
organization, intensity of networks or altruistic behavior - lags behind that in
developed countries. The differences in individual-leveI determinants cannot fully
account for the gap at the aggregate leveI. Once we also include aggregate measures
of economic development and quality of institutions, the gap disappears. This implies
that the EU enlargement will contribute to a convergence in social capital, assuming
that it contributes to the economic and institutional development of Eastern European
countries. A necessary condition is that both, formal and informal institutions and
their interaction should be regarded in this processo
Keywords: social capital, institutions, capitalism, transition
JEL codes: Z13, P37, 057, 017
v This research was initiated while Jan Fidrmuc was visiting AIAS whose hospitality he gratefully acknowledges. We are indebted to Robert Manchin of The Gallup Organisation Europe for giving us access to the Candidate Countries' Eurobarometer survey data.
• ECARES, Université Libre de Bruxelles; ZEI, University of Bonn; CEPR, London; and WDI, University of Michigan. Contact information: ECARES, Université Libre de Bruxelles, 50 A venue F.D. Roosevelt, CP 114, 1050 Brussels, Belgium. Email: [email protected]. Phone: +32-2-650-4462, Fax: +32-2-650-3369 .
1 Introduction
Over the last decade, social capital has been at the focus of attention of an increasing
number of sociologists, political scientists and economists, resulting in a growing
awareness of its importance for the deve10pment of an economy. According to the
World Bank, social capital shapes the quality and quantity of a society's social
interactions (The World Bank, 2002). According to Chhibber (2000: 296), "social
capital constitutes the informal mIes and norms that along with the formal mIes
establish the institutional framework determining economic outcomes."From a
comparative point of view, Coleman (1988) argues that social capital, like other forms
of capital, is productive and facilitates the attainrnent of goals that otherwise would
not be possible. More specifically, high stock of social capital increases individuaIs'
ability and willingness to cooperate, improves monitoring and enforcement of
contracts, and results in less information asymmetry. Social capital therefore lowers
transaction costs, fosters innovation and dissemination of technology and thus leads to
better economic outcomes.
In this paper, we compare and analyze the stock of social capital in two regions:
the current member countries ofthe European Union, and the new member and
candidate countries that are part of the current enlargement process 1. Though there is
some research on social capital in both current and new member states separately, to
the best of our knowledge, we are the first to systematically develop measures
applicable to both groups and use these in an analysis pertaining to the enlargement
processo So far, the focus when studying the enlargement has been on real and
nominal convergence and convergence in formal institutions (i.e., laws and
regulations). Informal institutions (i.e., norms, relationships, and mIes of behavior)
have not been studied in a stmctured way, however. Yet, new institutional economics
provides an extensive analysis ofthe importance of informal institutions and their role
in explaining differences across developed and undeveloped countries. Given that
new member states are still going through transition, involving tremendous
institutional restructuring, it is very important that informal institutions develop
parallel to formal institutions, so that the two remain compatible. If this happens, the
transaction costs of this institutional restmcturing - expressed in the form of predatory
I The analysis includes the ten countries scheduled to enter in May 2004 (Cyprus, Czech Republic,
activities such as corruption and tax evasion - will decrease (Pejovich, 2003). On the
other hand, if formal and informal institutions are in conflict, more of such predatory
activities may be expected as shown empirically by Gerxhani (2004).
This paper recognizes the importance of both formal and informal institutions by
looking at social capital as one of the significant factors determining the effects of EU
enlargement. The existing literature2 mainly studies the effect of social capital on the
economic and institutional development of a country. Little, if any, attention is given
to what determines the stock of social capital. By filling this gap, this paper
contributes to the literature on social capital as well as to the discussions about the EU
enlargement. It does so:
1. by providing a comparative analysis of the formation of social capital in both
current and new member states;
2. by explaining the difference in the leveIs of social capital in the two groups of
countries;
3. by exploring the effect that the enlargement of the European Union will have
on the stock of social capital in the new member states.
The paper is organized as follows. The next section provides an overview of
analytical findings about the importance of social capital in general and more
specifically in the current and new member states. Section 3 introduces the data and
methodology our analyses are based on. Section 4 presents the empirical analysis and
discusses the results. Section 5 concludes.
2 Does Social Capital Matter?
As a consequence of the variety of aspects it covers, social capital is defined in
various ways. Although the concept itself originates from Loury (1977) and later
Bourdieu (1986), Coleman's (1988) definition has beco me the most popular.
Coleman, presenting a sociologist's view, defines social capital as a component of
human capital that allows members of a given society to trust one another and
cooperate in the formation of new groups and associations (Coleman, 1988). Putnam
(1993), presenting a political scientist' s view, describes social capital as "features of
sociallife - networks, norms, and trust - that enable participants to act together more
effectively to pursue shared interests" (664-665). Stiglitz (2000), presenting an
economist's view, sees social capital - consisting of tacit knowledge, number of
networks and accumulation of reputation - as a social means to tackle moral hazard
and incentive issues. Broadly speaking, alI these definitions refer to trust, cooperative
behavior, and networks between groups, as essential components of social capital
(Knack and Keefer, 1997). In the presence of trust, cooperation will be easier and
therefore the frequency and density of networks is expected to be higher. 3 Interaction
through networks in turn enhances trust and cooperative ability. According to
Dasgupta (1988), social capital can make economic transactions more efficient by
giving parties access to more information, enabling them to coordinate activities for
mutual benefit, and reducing opportunistic behavior through repeated transactions. In
addition, Putnam (1993) argues that participation in civil associations can contribute
to the effectiveness and stability of democratic govemment, both because of their
'internaI' effects on individual members and because oftheir 'externaI' effects on the
wider polity. "InternalIy, associations instill in their members habits of cooperation,
solidarity, and public-spiritedness. ExternalIy, 'interest articulation' and 'interest
aggregation' are enhanced by adense network of secondary associations" (Putnam,
1993: 89-90).
The economic and institutional development of a country may influence social
capital. Grief (1994) reports that according to social psychologists, societal
organization is highly correlated with per capita income. He argues that, currently,
most of the undeveloped countries are 'colIectivist' while developed countries are
'individualist'. ColIectivist societies are characterized by individual interactions
among specific religious, ethnic or family-based groups, whereas cooperation
between members of different groups is non-existent. Contract enforcement is
accomplished primarily through informal mechanisms. Individualist societies, instead,
are characterized by interactions among individuaIs from different groups, where
individuaIs shift easily from one group to another. Contract enforcement is achieved
mainly through institutionalized organizations (e.g., the court). Grief conc1udes that
"the colIectivist system is more efficient in supporting intra-economy agency relations
and requires less costly formal organizations but it restricts efficient inter-economy
agency relations, whereas the individualist system does not restrict inter-economy
agency relations but is less efficient in supporting intra-economy relations and
requires costly formal organizations" (Grief, 1994: 942).
This categorization of Grief can be applied to the two groups of countries
analyzed in this paper. The characteristics of collectivist societies can be found in the
new EU members, while the features of individualist societies can be observed in the
current member states. More specifically, based on Griefs work and some additional
research 4, social capital in developed countries (current member states) can be
characterized by a high density of economic transactions among different groups,
well-established institutions, high level of generalized trust and participation in civil
associations, and a bottom-up structure of economic transactions. Social capital in the
less developed post-communist societies (new member states)5 can be characterized
by negative outcomes (i.e., gray economy, corruption and state failure), low leveIs of
generalized trust and participation in civil associations, and a top-down structure of
economic transactions.
Differences in formal institutions have often been mentioned as important causes
of different leveIs of social capital even within the group of developed countries or
within a developed country itself (see for example, Fukuyama, 1995 or Putnam et aI.,
1993). However, these differences are considered to be even stronger when
comparing a developed country to a transition country. Because individualist societies
(i.e., current member states) are characterized by an interaction between different
individuaIs from different groups, formal enforcement institutions were needed in
order to match and encourage informal institutions like norms of collective action.
Many of these countries6 have had an opportunity to establish a civic society for
centuries. Most of new members (transition countries), on the other hand, come from
a completely different historical and institutional background. Social capital in
transition countries is described in detail by Paldam and Svedsen (2000, 2001), Raiser
(1999) and Kunioka and Woller (1999). They put forward a theory called the
dictatorship theory of missing social capital. According to this theory, dictatorships
destroy social capital. Moreover, they create such conditions that even when
4 See Knack and Keefer (1997), Pejovich (1993, 2003), Paldam and Svendsen (2000), and Bakacsi et aI. (2002).
5 We are aware of the fact that not all new member and candidate countries are former communist countries. Therefore, we check the robustness of our conclusions by replicating all steps of our analysis while omitting Cyprus, Malta and Turkey.
dictatorships collapse, social capital may develop negatively and impede economic
growth. During the communist dictatorship in most of the new EU members,
'positive' social capital decreased and moreover, an increase of 'negative' social
capital took place. This 'negative' social capital was observed in the form of
underground activities, corruption or bribing. The gap, created by the sudden
destruction of old institutions and the creation of new ones, provided an attractive
environrnent for the persistence of 'negative' social capital during transition.7 According to Paldam (2002), more corruption leads to lower generalized trust. He
argues that corruption is by far the best available measure of 'negative' social capital.
Acknowledging institutional differences, this paper first verifies empirically
whether the stock of social capital is different in current member states than in new
members. This is followed by an empirical analysis of the determinants driving these
differences. We start with a description of the data and methodology and the way
social capital is operationalized.
3 Data and Methodology
The analysis is based on a number of recent Eurobarometer surveys commissioned by
the European Commission and carried out by Gallup Europe. In particular, we use
data from the Spring 2002 Candidate Countries Eurobarometer (CCEB), a survey
covering all 13 new members8, and data from multiple Standard Eurobarometers
(EB), carried out in all EU member countries in 1998, 1999 and 2001.9 The CCEB
survey includes responses of 14,163 individuaIs: approxirnately 1,000 respondents per
country, except for Cyprus and Malta with 500 respondents each and Poland and
Turkey with 2,000 each. The EB surveys range between 15,943 and 16,224
respondents. Each country is represented again by approximately 1,000 respondents,
except Luxembourg with 500. Furthermore, two regions are reported as separate
entities: Northem Ireland (300 observations) and Eastem Germany (1,000
7 The extent to which this 'negative' social capital (i.e., underground activities or corruption) took place varied per country. Rose (2000) relates it to the supremacy of the totalitarian regime these countries experienced during communism. The same line of argument can be found in Putnam et aI. (1993), where the low leveI of social capital in South Italy is attributed to the long absolutist regime of the Kingdom of Sicily.
8 Although Bulgaria and Romania will probably join the EU in 2007, and Turkey even later, given that their current status is as candidate countries, we include them in the analysis.
respondents). Besides questions relevant for measuring social capital, the surveys also
report extensive information on the respondents' socio-economic and demographic
characteristics. The surveys were carried out by face-to-face interviews and are
broadly representative at the national leveI (see WZB, 2003).
Social capital is typically measured by means of three alternative proxies:
participation in voluntary organizations, clubs and associations; presence of trust; and
density of networks (see the survey by Paldam and Svendsen, 2000). Civic
participation, also dubbed Putnam 's instrument (after it was popularized by Putnam,
1993), measures the degree to which people willingly interact with each other by
participating in clubs (including hobby and sports clubs), professional associations,
charities, neighborhood councils, or religious organizations.1O Trust measures the extent to which people find strangers trustworthy. Networks, on the other hand,
measure the density of ties between individuaIs, which can be used for the purpose of
pursuing intended actions (see Lin, 2001 for more). While the three proxies are
measured differently, they tend to be very strongly correlated (Putnam, 2001).11
In this paper, we focus on the micro leveI of social capital. Anirudh and Shrader
(1999) argue that at this level, horizontal organizations and social networks contribute
to collective and transparent decision making processes. Given the debate on whether
associational activities or Putnam's instrument is a good representation of social
capital (see Jackman and Miller, 1998), we use various measures of social capital.
Obviously, our choice of proxies for social capital is dictated by the availability of
suitable questions in the surveys we use. No question on trust was included in the
Eurobarometer surveys. They do, however, contain extensive information on the
respondents' active participation in various voluntary organizations. Specifically, the
precise wording of the question is "From the following tist, could you tell me in which
of these organizations do you actively participate?" The respondents were asked to
indicate whether they participate in any of the following: charities (social, communal
or religious); religious or parish organizations other than charities; cultural or artistic
organizations; trade unions or political parties; human rights movements or
10 The relationship between membership in associations and social capital has already been recognized earlier, however. For example, Bourdieu (1986) identifies social capital as assets gained through memberships in networks, while Coleman (1988) defines it as an additional outcome of an organization, which might have originally been established for other purposes.
11 A number of analysts have recent1y focused on trust to measure social capital, largely because the
organizations; organizations for the protections of nature, animaIs and the
environment; youth organizations such as scouts or youth clubs; consumer
organizations; sports clubs and associations; hobby clubs; and other clubs or
organizations. It is important that the question specifically asks the respondents to list
those organizations in which they actively participate rather than those that they are
members of. We believe the former gives a better indication of participation than the
latter. For our analysis, we counted the total number of organizations that the
respondents actively participated in. Very few individuaIs participate in more than 3
organizations. Therefore, we recoded this measure so that it takes values O, 1, 2, or 3,
with the last being ascribed to anyone who participates in three or more organizations.
Our second proxy for social capital measures the presence of social networks that
one can rely on in need. Specifically, the respondents were asked
"lf
you had any ofthe following problems (you were feeling depressed; you needed help finding a job for
yourself or a member of your family; or you needed to borrow money to pay an urgent
bill, like electricity, gas, rent or mortgage) is there anyone you could rely on to help
you, from outside your own household?" As these three networks are rather different
in nature, we codify each as a separate binary variable taking value 1 if the individual
reports having access to the network in question and O otherwise.
FinalIy, we also use a measure of altruism. Putnam (2001) presents evidence for
the United States showing that philanthropic generosity is strongly correlated with
social capital as measured by civic participation. Our measures of altruism are based
on answers to the folIowing two questions: "Now thinking about poor or socially
excluded people, in the last twelve months, have you done the following (given money
or goods to poor or socially excluded people; given up some of your time to help poor
or socially excluded people) at least once a month, less often or have you not done
it?"
Data for all three types of measures of social capital are available for all 13 new
member states in the Spring 2002 CCEB survey. Unfortunately, no single Standard
EB survey (covering the current member states) contained alI three types of questions.
Therefore, we colIected available data for the current EU members from three
different Standard Eurobarometer surveys, conducted in 1998 (civic participation),
2001 (social networks) and 1999 (altruism). Hence, although social capital proxies for
the new and current EU members are constructed using data from different years, the
questions asked in the current and new members is the same, despite the time gap). As
social capital is unlikely to change much in the course of a few years, we believe we
can use the data in a comparative analysis involving both current and new members of
the European Union.
Table 1 presents average values of the aforementioned six indicators of civic
participation, social networks and altruism, in descending order, for both the current
and new member states. The average values for the two groups are also included. Two
observations can be made. First, as hypothesized, the current member countries tend
to be better endowed with social capital than the new members: for five categories out
of the six, the EU average is higher than that for the new member countries. Second,
there is a considerable degree of variation within both groups of countries - some new
member states have very favorable endowments of social capital whereas some EU
member countries fare rather poorly. This variation has been predicted before. Paldam
and Svendsen (2000), for example, argue that the differences could be explained by
the fact that social capital has the tendency to stay in certain equilibria. The dynamics
ofthese equilibria are explored empirically in the following section.
TABLE 1 HERE
4 Results
In the preceding section, the average values for six indicators of social capital
revealed a gap between the current and new members of the EU. In this section, we
investigate the factors that underlie this gap. While the gap was presented above with
aggregate data, we carry out our analysis at the individual leveI so as to improve our
understanding also of the micro-determinants of this variance.
As a first step, we relate the individual endowments of social capital to a number
of potential socio-demographic determinants at the individual leveI: gender, age,
marital status, education, occupation, residency in urban vs. rural areas, and income.
To account for country-specific factors, we also include country dummies (note that
East Germany and Northem Ireland are reported as separate countries in the EB data
sets - a distinction that we retain to account for the possibly special nature of these
presents those for the current EU member states.12 A number of individual
characteristics appear to have an important impact on the stock of social capital.
Furthermore, the determinants of social capital tend to be similar in the current and
new member countries of the EU. Education appears particularly important:
respondents with higher education or those who are still studying are more likely to
participate in voluntary organizations, have social networks at their disposal, and
behave altruistically. Not only are the same variables significant and have the same
signs but also the size of coefficients is similar across the two groups of countries.
The impact ofincome (measured as nationally-defined income quartiles) on social
capital is again similar in the current and new members: individuaIs with higher
income tend to have higher rates of civic participation, greater access to networks and
contribute money to those in need. The only exception is contributing one's time: the
propensity to give up one's time for philanthropic reasons rises with income in the
new members while the opposite holds for the current members.
Occupation and employment status also seems important for the formation of
social capital, however, with the differences between the two groups of countries
somewhat more pronounced. Thus, those in white-collar jobs tend to participate more
often in the new members whereas in the current members they stand out mainly
because of better social networks. Respondents who are currently unemployed (or
reported a history of unemployment in the past), in contrast, report lower rates of civic
participation and, in the current member countries, also have less access to social
networks. These results go along with the general predictions in the literature. An
interesting result, however, concems the positive correlation we observe between
self-employment and social capital. "The fundamental source of change is leaming by
entrepreneurs of organizations" (North, 1993: 6). Given the structural changes
transition countries are going through, the entrepreneur can play a criticaI role in this
processo As argued by Pejovich (2003) and indicated by our results, entrepreneurs can
contribute to a society where performance is rewarded and individual liberties are
promoted. As a result, by bridging the capitalist culture with the current one in
transition countries, self-employment may contribute to a smooth EU enlargement
processo
TABLES 2 AND 3 HERE
The models estimated for the new and current member countries thus appear
qualitatively very similar. Nonetheless, country-specific effects account for a
considerable portion of the differences in individual stock of social capital, as
evidenced by the high and significant country dummies. To see whether the new
member states still appear to lag behind the current ones after controlling for
individual determinants of social capital, we merge the data for both groups and
include a dummy variable distinguishing new members (while dropping the country
dummies). Should the 'new member' dummy be insignificant, this would indicate that
the gap between the new and current members can be fully explained by differences
in individual characteristics such as educational attainment, employment and
occupational status.
The results are reported in Table 4. The coefficients estimated for individual
determinants of social capital are again very similar to those obtained in separate
regressions for the current and new members. However, the dummy for new members
appears with a negative and strongly significant coefficient, indicating that even after
controlling for individual-Ievel sources of variation in the stock of social capital, the
new member states stilllag behind the current EU members.
TABLE4 HERE
This brings us to the second step ofthe analysis. To investigate whether the gap in
social capital between EU new and current countries is due to the differences in the
leveI of economic development and/or quality of institutions, we proceed by including
a number of aggregate variables in the analysis: GDP per capita (in
purchasing-power-parity terms); the Gini coefficient of income inequality; the Transparency
Intemational corruption-perception index (inverted so that higher values indicate
lower corruption); the average of indexes of political freedom and civil liberties
reported by the Freedom House (in altemative regression specifications, we replaced
this democracy index with a measure of the fraction of years since 1972 that the
country was classified by the Freedom House as free or partially free); and the
average economic growth over preceding three years. While we tried several
one.13 The most important finding is that once these aggregate indicators of economic development and institutional quality are included, the new members no longer appear
different from the current EU members with respect to their stock of social capital. In
fact, already by controlling only for the GDP per capita, the significance of the new
member dummy all but disappears (it is negative and significant at the 10% leveI for
networks for finding employment, and significant and positive at the 10% leveI for
contributing one's time to help the needy). In the regressions reported in Table 5, the
variable measuring availability of social networks for finding employment appears
negative and marginally significant (at the 10% level). In contrast, when accounting
for aggregate factors, the new members in fact display significantly higher rates of
civic participation than the current members.
TABLE 5 HERE
While the aggregate variables succeed in driving down the significance of the
new members dummy, they themselves do not appear consistently significant across
the various regression specifications we tried.14 The extent of corruption, in particular,
appear to exert an important impact on cross-country variation in the stock of social
capital, appearing with positive sign in five regressions, with its impact on civic
participation and networks for borrowing being strongly significant. Importantly, the
individual socio-demographic attributes (education, occupation, unemployment and
income) remain strongly significant afier controlling for aggregate determinants of
social capital.
5 Conclusion
The existing literature on social capital is mainly focused on the effect of social
capital on the economic and institutional development of a country. Using recent
survey data on civic participation, the existence of social networks, and altruistic
behavior, this paper studies the determinants of social capital in Westem (EU current
members states) and Eastem (EU new member states) European countries. The results
identify important differences in the stock of social capital between these two groups
13 Additional results can be obtained from the authors upon request
of countries within Europe. The analysis reveals, however, that while the formation of
social capital at the individual levei is affected by very similar factors in both groups
of countries, the differences in individual-levei determinants cannot fully accounted
for the gap at the aggregate leveI. However, once we also include aggregate measures
of economic development and quality of institutions, as indicated by the literature on
social capital and institutional economics, the gap disappears. This finding thus
indicates that the gap in social capital between Eastem and Westem Europe can be
largely attributed to economic and institutional differences. The effect of corruption
points to the importance of informal institutions in this institutional disparity. This
impli
es that although a convergence in formal institutions between current member states
and new members has to a large extent been accomplished, there is still a conflict
between these 'harmonized' formal institutions and the existing informal institutions
in the new member states. This clash, expressed in the form of corruption or other
predatory activities, contributes to a significant divergence with respect to social
capital.
The expectation is that the enlargement of the European Union will contribute
to more open democratic govemments and policies in the candidate countries. This
will, in tum, promote public policies that discourage rent-seeking opportunities,
motivate a rewarding scheme of leaderships based on performance, a generalized
public trust on state's actions, and a civic spirit. In other words, once Eastem
European countries catch up with the West in terms of economic development and
institutions, they are very likely to close the gap in social capital as well. For this to be
possible, however, the importance of the interaction between formal and informal
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Stiglitz, lE., 2000. Formal and informal institutions, in Dasgupta, Partha and Ismail Serageldin, eds., Social Capital: A Multifaceted Perspective, pp. 59-71, The World Bank, Washington.
The World Bank, 2002. Social Capital for Development. Available at http://www.worldbank.orglpoverty/scapital/index.htm.
Table 1: Alternative measures of social capital
A verage Participation Network: Depressed Network: Job Network: Money AItruism: Money AItruism: Time
Sweden 2.000 lreland 0.934 lreland 0.863 lreland 0.911 Northem Ireland 1.288 Romania 0.669
Denmark 1.781 Netherlands 0.924 Spain 0.798 Spain 0.910 Malta 1.221 Cyprus 0.635.
Netherlands 1.701 Spain 0.920 Netherlands 0.789 Sweden 0.904 lreland 1.169 Luxembourg 0.559 Finland 1.238 Sweden 0.912 Luxembourg 0.744 Netherlands 0.879 Netherlands 1.088 Finland 0.553 Luxembourg 1.027 Denmark 0.896 Denmark 0.743 Denmark 0.874 Romania 1.079 Netherlands 0.541 Czech Republic 0.938 Slovakia 0.895 Austria 0.740 Northem lreland 0.849 Cyprus 0.931 Ireland 0.507 Germany-West 0.928 Northem lreland 0.889 Northem lreland 0.739 Finland 0.839 Luxembourg 0.927 Slovenia 0.496
EU Average 0.912 Great Britain 0.879 Portugal 0.730 Italy 0.818 Great Britain 0.920 Turkey 0.494
Northem lreland 0.904 France 0.875 Great Britain 0.721 Czech Republic 0.799 Italy 0.917 Austria 0.485 Great Britain 0.882 Czech Republic 0.863 Slovenia 0.721 EU Average 0.796 Poland 0.895 Hungary 0.434 Austria 0.878 EU Average 0.856 Italy 0.701 France 0.792 Lithuania 0.886 lNorthem lreland 0.419
Slovakia 0.864 Luxembourg 0.855 EU Average 0.699 Slovakia 0.791 Spain 0.867 Poland 0.405
lreland 0.838 Italy 0.848 France 0.695 Slovenia 0.788 EU Average 0.841 EU Average 0.397
Belgium 0.726 Finland 0.848 Czech Republic 0.670 Portugal 0.788 Finland 0.840 CC Average 0.389
Cyprus 0.720 Austria 0.844 Sweden 0.658 Great Britain 0.786 Turkey 0.821 Italy 0.386
Slovenia 0.701 Malta 0.840 Belgium 0.653 Luxembourg 0.778 Greece 0.819 Greece 0.382
Malta 0.693 Portugal 0.839 Hungary 0.625 Estonia 0.774 Austria 0.781 Malta 0.380
France 0.578 Poland 0.832 Finland 0.608 Poland 0.765 France 0.749 Portugal 0.372
Estonia 0.574 Belgium 0.811 Germany-West 0.606 Austria 0.757 Sweden 0.743 Lithuania 0.348
CC Average 0.545 Germany-West 0.805 Cyprus 0.589 Hungary 0.728 CC Average 0.729 Latvia 0.343
Germany-East 0.541 Hungary 0.802 Greece 0.558 Greece 0.698 Denmark 0.716 Belgium 0.335
Italy 0.494 Slovenia 0.782 Germany-East 0.545 CC Average 0.697 Slovenia 0.700 Spain 0.325
Lithuania 0.484 Germany-East 0.781 Poland 0.531 Lithuania 0.679 Portugal 0.659 Great Britain 0.324 Latvia 0.466 CC Average 0.776 CC Average 0.525 Romania 0.677 Belgium 0.651 Germany-East 0.321
Turkey 0.425 Estonia 0.772 Slovakia 0.506 Germany-West 0.676 Hungary 0.646 Denmark 0.314
Hungary 0.397 Lithuania 0.766 Lithuania 0.504 Bulgaria 0.669 Germany-East 0.596 Germany- West 0.312
Poland 0.355 Romania 0.725 Malta 0.502 Belgium 0.660 Latvia 0.593 France 0.303
Spain 0.349 Turkey 0.707 Estonia 0.485 Cyprus 0.645 Germany- West 0.571 Sweden 0.303
Portugal 0.337 Latvia 0.706 Turkey 0.479 Germany-East 0.616 Slovakia 0.524 Slovakia 0.264
Greece 0.310 Bulgaria 0.702 Romania 0.446 Latvia 0.604 Czech Republic 0.447 Estonia 0.223
Romania 0.290 Cyprus 0.697 Latvia 0.400 Turkey 0.580 Estonia 0.413 Czech Republic 0.202
..
Table 2: Individual determinants of social capital in EU new member states
Networks ir Altruism: Altruis ~: Civic Networks ir in Need of Networks to Contribute Contrib te Participation Depressed Jobs Borrow Money Ti ne
Constant 1.660* 0.622** 1.903*
Female -0.291 * 0.330* -0.092* 0.048 0.215* 0.078 **
Married -0.164* 0.106** 0.055 0.l34* 0.080* -0.18 8*
Age 0.005 -0.034* -0.040* -0.044* 0.037* 0.05 8*
Age squared -0.0001 0.0002* 0.0003* 0.0003* -0.0003* -0.000 5*
Children -0.016 0.027 0.011 0.058* 0.002 -0.0 14
HH Size -0.032 -0.l56* -0.134* -0.l83* -0.029 0.0 27
Secondary 0.290* 0.l59* 0.144* 0.288* 0.279* 0.21 6*
University 0.752* 0.301 * 0.342* 0.425* 0.501 * 0.41 8*
Student 1.018* 0.601 * 0.288* 0.374* 0.181 ** 0.37 4*
Self-employed 0.206* 0.069 0.257* 0.269* 0.258* 0.20 2*
White collar 0.122** 0.072 0.l92* 0.l34 0.179* 0.14 3*
House person -0.435* -0.142 -0.206* -0.108 -0.029 0.0 71
Unemployed -0.273* -0.042 -0.l78* -0.129 -0.079 -0.0 27
Retiree -0.269* 0.048 -0.071 -0.08 0.074 -O .05
UE History: 1 -0.303* -0.l34** -0.293* -0.116 -0.117** -0.1 08 UE History: 2+ -0.092 -0.321 * -0.286* -0.336* -0.034 0.1 19 HH Income 2nd Quartile 0.189* 0.320* 0.358* 0.307* 0.291 * O.l 01 HH Income 3rd Quartile 0.346* 0.434* 0.438* 0.505* 0.421 * 0.1~ 2* HH Income 4th Quartile 0.442* 0.779* 0.929* 0.850* 0.754* 0.2 9* Small/Medium town -0.054 -0.03 -0.08 -0.105** 0.l99* -O.H 4*
City -0.328* 0.078 0.034 -0.103** 0.224* -0.2' 4*
Cyprus 1.634* -0.156 0.845* -0.252** 1.967* 1.8~ 5*
Czech Rep. 1.907* 0.847* 1.051 * 0.377* 0.486* O.l 37
Estonia 1.119* 0.049 0.189** 0.181 0.381* 0.3~ 7*
Hungary 0.986* 0.419* 1.089* 0.168 1.167* 1.2ç 9*
Latvia 1.037* -0.194** -0.088 -0.539* 0.824* 0.8~ 0*
Lithuania 1.095* 0.002 0.275* -0.352* 1.655* 0.9~ 6*
Malta 1.614* 0.808* 0.393* -0.536* 2.727* 1.1S 3*
Poland 0.498* 0.641 * 0.470* 0.309* 1.899* 0.9 1*
Romania 0.435* -0.05 0.266* -0.143 2.263* 1.9~ 5*
Slovakia 2.004* 1.240* 0.556* 0.488* 0.791 * 0.7L 0*
Slovenia 1.501* 0.182 1.295* 0.256* 1.237* 1.2~ 0*
Turkey 0.682* 0.182 0.596* -0.297* 1.998* 1.6~ 5*
,
..
Table 3: Individual determinants of social capital in EU current member countries
Networks if Altruism: Altruisl1~:
Civic Networks if in Need of Networks to Contribute Contribu e Participation Depressed Jobs Borrow Money Tin e Clubs Depress. Jobs Borrow Money T"me
Constant 1.505* 1.523* 0.794*
Female -0.245* 0.558* -0.043 0.189* 0.375 * 0.35 7*
Married 0.022 -0.051 0.046 -0.004 0.120 * O. 36
Age 0.041 * -0.027* -0.039* -0.025* 0.054 * 0.05 1 *
Age squared -0.0004* 0.0002 0.0001 * 0.0001 0.000 * 0.000 4*
Children -0.034 -0.078 * -0.14 7*
HH Size 0.031 0.083 * 0.08 7*
Secondary 0.286* 0.212* 0.172* 0.095 0.145 * 0.111 **
University 0.830* 0.394* 0.294* 0.209* 0.497 * 0.44 0*
Student 1.010* 0.713* 0.379* 0.540* 0.575* 0.44 6*
Self-employed -0.055 0.295* 0.081 0.287* 0.136** 0.22 4*
White collar 0.094 0.305* 0.123** 0.265* 0.217* O. 09
House person -0.204* 0.062 -0.081 0.131 0.270* O. 06
Unemployed -0.167** -0.273* -0.732* -0.313* 0.044 -O. 32
Retiree -0.103 0.019 -0.113 -0.031 0.329* O. 75
HH lncome 2nd Quartile 0.248* 0.302* 0.303* 0.229* 0.332* 0.13 2* HH lncome 3rd Quartile 0.641 * 0.388* 0.479* 0.536* 0.382* 0.1 HH lncome 4th Quartile 0.742* 0.542* 0.618* 0.662* 0.604* -O. D39
Small/Medium town -0.065 -0.139* -0.078
City 0.009 -0.019 0.02
Denmark 1.721* 0.696* 0.216** 1.310* 0.292* -O. D97
Germany West 0.556* 0.084 -0.213** 0.264* 0.004 O. D02
Greece -0.962* -0.492* -0.377* 0.341* 0.696* O.4C 1 *
Italy -0.419* 0.291 ** 0.257** 0.961 * 0.962* 0.3 6*
Spain -0.699* l.141* 0.666* 1.809* 1.035* 0.234 **
France -0.279* 0.607* 0.165 0.855* 0.535* O. 12
lreland 0.541 * 1.495* 0.802* 1.562* 1.690* 0.7C 5 *
N-Ireland 0.504* 0.979* 0.31 1.342* 2.121 * 0.38 **
Luxembourg 0.751* 0.447* 0.348* 0.679* 1.045* 0.9t 2*
Netherlands 1.757* 1.227* 0.510* 1.628* 1.326* 0.7<1 7 *
Portugal -0.679* 0.324* 0.468* 0.857* 0.420* 0.3t 7 *
Great Britain 0.817* 0.722* 0.326* 0.959* l.162*
o.
42Germany East -0.197** -0.024 -0.394* 0.067 0.093 c.I7
Finland l.153* 0.236 -0.320* 1.148* 0.737* 0.8t 9*
Sweden 2.072* 1.078* 0.02 1.909* 0.395* -O. 47
Austria 0.483* 0.064 0.297* 0.481 * 0.733* 0.7' 5 *
..
oi
Table 4: Individual determinants of social capital: Pooled data
Networks if Altruism: Altruis
r:
Civic Networks if in Need of Networks to Contribute Contribu te Participation Depressed Jobs Borrow Money Tir ~eClubs Depress. Jobs Borrow Money Ti me
Constant 1.570* 1.429* 1.251*
Female -0.245* 0.421 * -0.063* 0.171 * 0.181 * O.l~ 9*
Married 0.044 -0.052 -0.008 0.022 0.032 -O.O~ 7*
Age 0.031 * -0.019* -0.034* -0.020* 0.044* 0.0' 1*
Age squared -0.0003* 0.0001 ** 0.0002* 0.0002* -0.0004* -O.OOC 4*
Children 0.033* -0.036* -0.0 9*
HH Size -0.055* 0.072* 0.0 8*
Secondary 0.529* 0.307* 0.l22* 0.299* 0.051 O.C 11
University 1.104* 0.431 * 0.270* 0.492* 0.306* 0.2 5*
Student l.365* 0.759* 0.331 * 0.611 * 0.276* 0.2~ 3*
Self-employed -0.154* 0.119 0.153* 0.205 0.293* 0.2~ 7*
White collar 0.123* 0.226* 0.215* 0.203* 0.235* O.C 77
House person -0.353* -0.024 -0.128* -0.l53* 0.534* O.3C 1*
Unemployed -0.442* -0.275* -0.587* -0.360* -0.077 -O.C 42
Retiree -0.329* 0.013 -0.100** -0.082 0.260* O.C 67
HH Income 2nd Quartile 0.178* 0.267* 0.297* 0.238* 0.304* 0.1 2* HH Income 3rd Quartile 0.311 * 0.337* 0.405* 0.438* 0.398* 0.1~ 7* HH Income 4th Quartile 0.410* 0.610* 0.768* 0.656* 0.717* 0.1 8*
Small/Medium town 0.023 -0.104 -0.051 *
City 0.011 * -0.045* -0.093*
New members -0.960* -0.559* -0.753* -0.536* -0.176* 0.1 1*
N.Cham. PIEPGE SA G387f Autor: Gerxhani, Klarita
Título: Formation of social capital in Eastem Europe
~
Table 5: Individual and aggregate determinants of social capital: Pooled data
Networks ir Altruism: Altruis ~: Civic Networks ir in Need or Networks to Contribute Contribl te Participation Depressed Jobs Borrow Money Ti ~e
Clubs Depress. Jobs Borrow Money Titme
Constant -0.115 1.404 0.002
Female -0.286* 0.417* -0.103* 0.101 * 0.256* 0.1 0*
Married -0.060 -0.023 -0.016 0.046 0.044 -0.08 **
Age 0.024* -0.024** -0.037* -0.027* 0.048* 0.0 9*
Age squared -0.0002* 0.0001 0.0002** 0.0002 -0.0004* -O.OO~ 5*
Children -0.040** -0.046* -0.0 2*
HH Size 0.046** 0.065* 0.0 6*
Secondary 0.300* 0.206* 0.071 0.168* 0.129**
o.
88University 0.763* 0.303* 0.200* 0.321 * 0.407* 0.3( 2*
Student 1.012* 0.621 * 0.250* 0.455* 0.369* 0.3 5*
Self-employed 0.163** 0.199** 0.190* 0.290* 0.261 * 0.2 1*
White collar 0.194* 0.250* 0.235* 0.241 * 0.227* 0.1 56
House person -0.157 0.052 -0.029 0.079 0.325* 0.20 **
Unemployed -0.344* -0.214* -0.552* -0.303* -0.089 -0,( 71
Retiree -0.194* 0.081 -0.052 0.018 0.288* 0,( 78
HH Income 2nd Quartile 0.177* 0.252* 0.275* 0.201 * 0.305* 0.08 ** HH Income 3rd Quartile 0.454* 0.328* 0.388* 0.406* 0.412* O. 14 HH Income 4th Quartile 0.490* 0.590* 0.768* 0.664* 0.722* O. 81
Small/Medium town -0.004 -0.098** -0.042
City 0.055 0.004 -0.025
GDP per capita 0.031 0.006 0.002 -0.029* 0.020 -O. 01
Gini coefficient -0.019 0.004 -0.010 -0.004 0.036
-o.
21N on-corruption 0.330* 0.109 0.056 0.219* -0.034
o.
38Democracy 0.108 0.101 -0.005 0.066 -0.044 -0.2 8*
Av. Growth -0.077 -0.034 0.018 0.041 0.025
o.
76New members 0.893* 0.013 -0.498** -0.192 -0.114
o.
63Notes: Estimated with logit or ordered logit, Significance leveis: * 5% and ** 10%.
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