social capital and collective memory

7/26/2019 Social Capital and Collective Memory

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Social Capital and Collective Memory:

A Complex Relationship

Sibylle Puntscher, Christoph Hauser, Karin Pichler and Gottfried Tappeiner*

I. INTRODUCTION

Social capital, i.e. the features of social organization such as networks, norms,

and social trust that facilitate coordination and cooperation (Putnam, 1995, 67),

is by now a central concept in most fields of social science. The term has been

discussed for both its theoretical foundation and its empirical operationalization.

At least in economic research, however, it has become an established concept. A

multitude of studies have analyzed the effects of social capital, in particular of

trust as well as strong and weak social networks, on various economic perfor-

mance indicators. Most studies conclude that general trust and weak social tiespositively affect the performance of nations (Zak and Knack, 2001, Whiteley,

2000) and regions (Beugelsdijk and Van Schaik, 2005, Dincer and Uslaner,

2010). Some contrary works also provide empirical evidence that social capital

can be detrimental for a society (Dasgupta, 2005). In general, however, higher

levels of social capital are associated with economic prosperity, low crime rates,

effective government and high local quality of life (Cento Bull and Jones, 2006,

Besser, 2009).

These beneficial effects highlight the importance of identifying the source of

social capital and the impact factors that affect its accumulation. In the literature,social capital is seen as being characteristic of individuals (Bourdieu, 1986) as

well as a property of social networks like firms, regions or nations (Putnam,

1993, Knack and Keefer, 1997, Westlund and Nilsson, 2005). Thus, it is neces-

sary to give similar consideration to individual and systemic factors as potential

driving forces of social capital.

* MMag. Sibylle Puntscher (corresponding author): Department of Economics, University of Innsbruck,

Universitaetsstr. 15, 6020 Innsbruck, Austria. E-mail: [email protected].

Dr. Christoph Hauser: Department of Economics, University of Innsbruck, Universitaetsstr. 15, 6020

Innsbruck, Austria. E-mail: [email protected]. Karin Pichler: Chamber of Commerce of Bolzano/Bozen, Via Alto Adige 60, 39100 Bolzano/

Bozen, Italy. E-mail: [email protected].

Professor Dr. Gottfried Tappeiner: Department of Economics, University of Innsbruck, Universitaetsstr.

15, 6020 Innsbruck, Austria. E-mail: [email protected].

KYKLOS, Vol. 67 February 2014 No. 1, 116132

116 2014 John Wiley & Sons Ltd.


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A particularly interesting approach to systemic influences is via a phenomenon

called collective memory (Rothstein, 2000). Collective memory can be defined

as the shared experiences of a community that can date back a long time but thattoday still has a significant impact on the current norms, behavior and beliefs of

the community with economic, political and social consequences (Dess, 2008).

These collective experiences can result from an ongoing process or from a

drastic shock.

This study partially explores the relationship between collective memory and

social capital in the setting of a comprehensive case study. Three regional

characteristics that can be seen to be the outcome of such common experiences

are examined as proxies for collective memory. Firstly, the current institutional

and legal framework is considered as a form of present or very recent experi-ences with systemic conditions. Secondly, cultural attitudes serve as proxy for a

groups long-term historical developments. Lastly, the assumption is pursued

that formative shocks such as natural disasters or political overthrows in recent

history might be socially memorized and thus still shape the present-day com-

munity. It is further hypothesized that negative shocks particularly affect a

societys level of general trust and that a shocked community adopts some

additional preventive measures with more or less long-lasting effects.

Data availability and the qualitative nature of shock effects and institutional

frameworks mean these hypotheses concerning collective memory and its impacton social capital can be tested only in a specific context. Therefore, the following

analyses were conducted in a regional case study, where particular historical

developments and cultural shocks allow a nearly natural experiment in order to

examine the effects of the various aspects of collective memory. This investiga-

tion area is composed of three neighboring regions in two countries, namely the

Provinces of Trento and Bolzano (the latter also known as South Tyrol) in Italy

and the State of Tyrol in Austria1. One region, the bilingual Province of Bolzano,

became part of Italy only in 1918 and was subsequently subject to massive

immigration and repression. Hence, it is possible to discriminate between thesystemic characteristics of collective memory by distinguishing various popula-

tion groups in the sample:

Current institutional framework: measured by the current national affiliation

of the regions.

Cultural attitudes: measured by the linguistic segmentation into the two

main languages German, spoken in Tyrol and partially Bolzano, as well as

Italian, spoken in Trento and partially Bolzano.

Historical shocks: In the 20th century the German-speaking population of

Bolzano suffered a severe shock when the region was separated from Austria

1. the three entities are referred to in this text as Trento, Bolzano and Tyrol.

SOCIAL CAPITAL AND COLLECTIVE MEMORY: A COMPLEX RELATIONSHIP

2014 John Wiley & Sons Ltd. 117


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and the peoples cultural values were subsequently oppressed. Simulta-

neously, Bolzanos Italian-speaking population first suffered a migration

shock and later a minority shock.2

The main question pursued in the analyses is the following: Is the conceptual

framework offered by the concept of collective memory able to identify not only

the effects of recent (i.e. institutional) or more long-term (i.e. cultural) ongoing

experiences, but also the impact of discrete shocks and their aftermath? The

impact of the various levels of collective memory is tested using four compo-

nents of social capital, namely Political Interest, Generalized Trust, Association

Activity and Friendship. Additionally, the parts of Italy and Austria not included

in the special investigation area are employed in the model as benchmarks. Thisallows us to examine whether the three regions are particularly affected by

historical developments or whether they merely reproduce the characteristics of

their nations.

For the ensuing analyses, the current literature on collective memory and the

main driving forces of social capital are discussed in Section 2. Section 3

presents in more detail the research area, its history and the dataset used for the

model. The methods applied are given in Section 4. Section 5 presents the main

results of the empirical analyses, while Section 6 discusses the findings and

concludes the paper.

II. LITERATURE

When analysing potential impact factors on an individuals integration in net-

works and on social attitudes, both individual and systemic characteristics are

commonly taken into account. The former are proxied primarily by personal

characteristics such as education, gender, age and occupation (cf. Alesina and La

Ferrara, 2002). While the evidence for the other indicators is mixed, there is

robust confirmation of the important role of human capital in shaping social trust

and interaction (Iyer et al., 2005, Letki, 2008). In addition to such individual-

level characteristics, the social capital of a person strongly depends on her or his

location in a particular community. The latter is henceforth referred to as the

systemic impact on social interaction.

The systemic properties analysed here as influencing the endowment of social

capital can partly be understood as the collective memory of a community

(Rothstein, 2000), because they are the result of common experiences in the

(distant or recent) past that affected the entire community and that still shape anindividuals attitudes, thereby inducing a common social behaviour in the

2. A more profound discussion of the historical development of the investigation area can be found in

Section III.1

SIBYLLE PUNTSCHER, CHRISTOPH HAUSER, KARIN PICHLER AND GOTTFRIED TAPPEINER



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present. Rothstein (2000) argues that social trust stems from the expectation that

other people will behave in a certain fashion. This expectation, however, is based

only on perceptions transmitted from our social environment by informationentrepreneurs such as politicians or journalists. Thus, the formation of collective

memories does not necessarily depend on direct links existing within a group and

is not automatically a cultural trait, but rather a strategic political process: . . .a

societys collective memory is contested political terrain, where different actors

try to establish their particular interpretation of the past as the collective memory

for the group (Rothstein 2000, 494).

Following Mohtashemi and Mui (2003), collective memory is a fundamental

source within networks of friends and acquaintances, from which people gather

additional social information to rationalize cooperation and make efficient deci-sions on altruistic behavior. Dess (2005) states that the beliefs of a younger

generation are strongly influenced by the information on social norms, values or

institutional quality passed on from the older generation. Similarly, Uslaner

(2008) finds for the US that general trust is inheritable depending on where a

persons grandparents came from. He states that the provenance of ancestors

matters more for a persons current general trust than does the persons current

neighbourhood. Hence, collective memory shapes young generations knowl-

edge of social capital and subsequently influences their attitudes and behaviour

in the present.Traditionally, the systemic-level approach to social capital in the literature

analyses the social and institutional structure of a region as well as a societys

culture as regional candidates for shaping social capital.

Models focussing on the impact of culture propose that historical and cultural

developments spanning hundreds of years shape the capacity of a society for

social cooperation and trust. The most famous study in this regard was conducted

by Putnam et al. (1993), who investigated the effectiveness of provincial gov-

ernments in Italian regions and found a strong north-south divide driven mainly

by cultural changes, namely the establishment of Norman kingdoms in the southand the development of free republics in the north. A similar study by Becker et

al. (2011) rooted in cultural factors found that a historical Habsburg affiliation

increases present-day trust and reduces corruption of courts and police. Thus,

collective memory in terms of culture, dating back even several centuries, is

found still to influence todays social capital.

The literature also shows that politics and government influence the social

trust and interaction of its citizens by supporting cooperation through well-

designed policies. Both Knack and Keefer (1997) and Berggren and Jordahl

(2006) found that the effective functioning of the legal system as measured byexecutive constraints, independence of courts or security of property

rights exerts a significant positive impact on social trust at the national

level.




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Moreover, population density is used as proxy for some structural features of

a society with potential effects on social interaction. The findings are ambiguous:

city life allows more social interaction (Borck, 2007, for Political Interest), butsimultaneously leads to a sense of social isolation, thereby reducing trust (Iyer et

al., 2005).

III. DATA

III.1. Investigation area

Our analyses require a sample that includes information on the various dimen-sions of social capital as well as its individual and systemic driving forces.

Furthermore, it should be possible to subdivide the dataset into various sub-

samples in order to analyse the effects of culture, social and institutional struc-

ture and historical shocks in various configurations.

Accordingly, we chose three adjacent political entities in the centre of the

European Union for our case study, namely the State of Tyrol (TIR), the Province

of Bolzano/Bozen (BZ) and the Province of Trento (TN). The location of these

regions in Europe is shown in Figure 1. Additionally, both Austria and Italy as

whole countries are included in the analyses as benchmark areas.This area fulfils the above-mentioned requirements and thus due to its histori-

cal and cultural development provides an almost unique laboratory for empirical

investigation of individual and systemic determinants of social capital (Magnani

and Struffi, 2009). More precisely, the characteristics of this dataset permit good

observation of the effects of culture, institutional environment and linguistic

heterogeneity on social capital, as other regional characteristics like topography,

income level or employment are similar for all three entities (cf. Appendix 1).

The three regions are subject to two different institutional environments, i.e.

Bolzano and Trento are both autonomous provinces of Italy, while Tyrol is anAustrian state. In Tyrol, the predominant language spoken is German, whereas in

Trento it is Italian. In Bolzano, however, 69.1% of the population is German-

speaking and 26.5% is Italian-speaking3. This permits four sub-groups to be

formed within the sample: German-speaking people in Tyrol, Italian-speaking

people in Bolzano, German-speaking people in Bolzano, Italian-speaking people

in Trento.

The current configuration with respect to language and institutional frame-

work is the result of historical events. The entire study area was part of the

Habsburg Empire until the end of World War I. In 1918, the area was split into

3. For the sake of completeness, the minority Ladin-speaking population in Bolzano should be mentioned.

Due to their small number and therefore small sample size, they were omitted from our analysis.




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a northern and a southern part: the State of Tyrol remained part of Austria,

whereas the newly created provinces Bolzano and Trento were annexed by Italy.

In the ensuing 20 years, the fascist dictatorship of Benito Mussolini attempted

to completely Italianize the Province of Bolzano. First, the South Tyroleans (i.e.

the German-speaking and Ladin populace) were culturally repressed and subjectto systematic cultural and linguistic assimilation and Italianization, usually

through repressive means such as the elimination of Tyrolean monuments and

traditions and the implementation of Italian as the only official language. In the

1930s, the fascist government additionally encouraged sustained immigration

from the other parts of Italy by offering attractive working and living opportu-

nities in order to create an Italian-speaking majority in Bolzano. As a result of

these strategies, the population of Bolzano increased from 7,000 Italian speakers

and 220,000 German speakers in 1910, to 80,000 Italian speakers and 235,000

German speakers in 1939. Thus, a new linguistic group was generated, namelythe Italian-speaking inhabitants of Bolzano.

After World War II the so-called Treaty of Paris established that Bolzano

remained part of Italy, but granted it wide-ranging autonomy in political,

Figure 1:

Tyrol-Bolzano/Bozen-Trento within Europe




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cultural, economic and social matters. To implement the treaty, the First

Autonomy Statute was passed in 1948 granting autonomy to the macro-region

Trento-Bolzano, where Italians, however, were still a majority. In the wake ofinternational pressure and the persistence of the South Tyroleans, the Second

Autonomy Statute was passed in 1972 and finally granted to the Province of

Bolzano alone substantial autonomy in legislative and administrative matters.

These historical developments have influenced the four linguistic sub-groups

quite differently. Tyrol lost a large portion of its territory, but was able to preserve

its affiliation with the newly created Austrian Republic and was thus spared

further historical shocks.

Trento, by comparison, viewed the annexation by Italy even positively, since

the large majority of the population was Italian-speaking and since in the early20th century efforts had already been made there by e.g. Cesare Battisti to achieve

autonomy and subsequently even to secede from the Austro-Hungarian Empire

(Forcher, 1984). Thus, the population did not experience shocks in the face of

subsequent developments.

The consequences of these historical changes, however, were formative for

Bolzanos two linguistic groups. The cession was a shock for the German-

speaking people of Bolzano, since they were no longer part of the country to

which they had belonged for over 500 years and to which they still felt attached.

Moreover, the systematic Italianization after 1920 and the sustained immigrationof Italians after 1930 were the second major blow for the South Tyroleans and

provoked large repercussions for social relations between the linguistic groups in

Bolzano. The First Autonomy Statute passed in 1948 was the third traumatic

experience as the German-speaking population remained a minority in the

macro-region Trento-Bolzano and continued to be subject to decision-making by

the Italian majority, at least until the Second Autonomy Statute was passed in

1972.

In contrast, the Italian-speaking population of Bolzano was generated mainly

by the immigration encouraged by Mussolini in the 1930s and also experienceda major shock due to immigration, the resulting loss of social networks and the

Second Autonomy Statute of 1972, which suddenly made them a minority within

the province (Gruber, 1995).

These contemporary historical events support our choice of these regions as an

appropriate laboratory for this case study. Because of their institutional, linguis-

tic and historical configuration, the three regions Tyrol, Bolzano and Trento are

well-suited as a setting in which to investigate the effects of collective memory

in terms of institutional framework, culture and traumatic collective experiences,

but also of social heterogeneity, while the other regional characteristics remainednearly equal. Conceivable proxies for culture are the language as well as the

regional experiences under Habsburg Rule. Table 1 briefly summarizes the rel-

evant regional features of the investigation area.




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III.2. Proxies for social capital and its impact factors

The data on social capital for the following analyses originate from two different

datasets. On the one hand, personal interviews were conducted by telephone in

the three regions Tyrol, Bolzano and Trento using questions from the European

Values Studies (EVS) (http://www.europeanvaluesstudy.eu/). This sample

amounts to 1,504 observations equally distributed over the three entities (i.e.

approx. 500 respondents in each area). Additionally, this special dataset is

enlarged by the EVS data for Austria and Italy (excluding the three separately

considered regions), which are then used as reference groups for the three

above-described entities. Finally, the overall sample used for the following

analyses comprises information on 4,917 respondents.

In accordance with other studies of social capital in Europe (Hauser et al.,

2007, Kaasa, 2009), we selected a range of questions on four dimensions of

social capital relating to interest in political affairs, social involvement (friend-

ship ties and group membership) and interpersonal trust. The questions selected

along with their proposed functions are illustrated in Table 2.

IV. METHODS

The social capital questions indicated in the previous section in Table 2 are

processed with a principal component analysis (PCA) with Varimax rotation.

This is done to develop composite indicators as recommended in the literature inorder to account for social capital as a multifaceted concept (Bjrnskov, 2006,

Sabatini, 2008, De Dominicis et al., 2011). The resulting components can be

interpreted as independent aspects of social capital that can be used to investigate

Table 1

Systemic properties of the investigation area

Language Habsburg Empire Institution Shocks

Austria German Yes Austria No relevant shocksTyrol German Yes Austria No relevant shocksBolzano German

populationGerman Yes Italy 1) Annexation (1918)

2) Fascism, Italianization3) 1st Autonomy Statute (1948)

Bolzano Italianpopulation

Italian No Italy 1) Immigration2) 2nd Autonomy Statute (1972)

Trento Italian Yes Italy No relevant shocksItaly Italian Noa) Italy No relevant shocks

a) Exceptions are parts of the Northern Italian regions of Lombardy and Veneto, which belonged to the

Habsburg Empire in the 19th century, however only for about 50 years, and the city of Trieste. Trento,however, was the only Italian region to already be part of the Holy Roman Empire and thus toexperience long-term influence of Austrian Rule dating from the Middle Ages.




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potential determinants. Working from the existing literature and available data,

we construct the model in Equation 1 to test the causal pathway leading to the

elaborated dimensions of social capital using the whole sample of observations:

SC Age Age Gender Education Occuij j j

ij

ij

ij

ij

= + + + + + 0 1 22

3 4 5 ppation

Urban Language Italy Bolzano

i

ji

ji

ji

j+ > + + + 6 7 8 95,000 ii

ji

ji i

jTrento Tyrol+ + + 10 11

(1)

where

SCij factorial value for social capital indicator j of individual i

Agei age in years of individual i

Genderi gender of individual i (1 =female, 0 =male)

Educationi highest level of education achieved by individual i

Occupationi employment status of individual i (1 =employed,

0 =unemployed)

Urban >5000i

individual i residing in town with more than 5,000inhabitants=1, 0 =otherwise

Languagei affiliation of individual i with linguistic group (1 =Italian,

0 =German) indicator for cultural attitudes

Table 2

Social capital dimensions with proposed function and selected measurement questions

Dimension Function Questions

Trust Perceived social distance toother people andexpectation of reciprocalcooperation

Generally speaking, would you say that mostpeople can be trusted or that you cant be toocareful in dealing with people?

On this list are various groups of people. Couldyou please sort out any that you would notlike to have as neighbors? (Variablerepresenting number of groups one wouldrather not have as neighbors)

PoliticalInterest

Interest displayed towardsocial affairs andwillingness to engage inpolitical activity

How important in your life: politics?How interested are you in politics?How important in your life: friends and

acquaintances?How often discuss politics with friends?

FriendshipTies

Integration in networks with ahigh degree of reciprocityand high frequency ofinteraction (strong ties)

How often spend time with friends?How often spend time with colleagues?

AssociationActivity

Integration in networksdominated by loosecontacts with diversepeople and low emotionalinvolvement (weak ties)

How often spend time in clubs and voluntaryassociations?

Do you belong to Group X? (Variablerepresenting number of memberships inindicated groups)




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Italyi individual i living in Italy =1, 0 =Austria proxy for the

institutional framework

Bolzanoi individual i living in the Province of Bolzano =1, 0 =otherwiseTrentoi individual i living in the Province of Trento =1, 0 =otherwise

Tyroli individual i living in the State of Tyrol =1, 0 =otherwise

ij disturbance term for individual i and social capital indicator j

The dependent variable SCij indicates the investigated dimension of social

capital. The independent variables represent individual characteristics and

affiliation with a particular group/location. The variable Age was modelled on

a curvilinear trajectory to account for lifecycle considerations. Education was

measured on an 8-point Likert scale4. The linguistic group, the particular regionand the urban environment are modelled with dummy variables. For the urban

environment we distinguished people living in locations with more than 5,000

inhabitants. This threshold is seen as a critical difference in the social structure

of the area. A further category for locations with more than 20,000 inhabitants

was computed, but did not change the fundamental results.

V. RESULTS

The PCA with Varimax rotation gives the rotated component matrix of the factor

loadings shown in Table 3. Following the Kaiser-criterion, four components with

an eigenvalue >1 are identified as exhibiting a highly significant Bartlett-Test of

Sphericity and a KMO criterion of 0.732. Overall, 63.28% of the variation in the

underlying questions is explained, which is in line with similar analyses based on

micro-data (Van Oorschot and Arts, 2005, Kaasa and Parts, 2008). The analysis

thus corroborates the presence of latent factors underlying the variables for social

interaction and social attitudes and allows the construction of proxy variables for

the four indicated dimensions of social capital.These extracted factor values were regressed on the listed determinants of

social capital. The overall explanatory power is in line with the literature on

individual values (cf. Costa and Kahn, 2001, R2 below 10%; Alesina and La

Ferrara, 2002, R2 equal to 11%). The estimation results are shown in Table 4.

The results indicate that considerable individual differences exist between the

four social capital factors (R2 between 20% and 8%) and that it is possible to

detect highly significant influences exerted by the analyzed impact factors. These

influences are discussed briefly for each social capital component individually.

4. Education was also measured with dummy variables, each covering a particular education level.

The findings (not shown here), however, did not change and thus the more parsimonious model is

maintained.




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Austria (without its separately considered region Tyrol) continues to serve as

benchmark for interpretation of the effects of collective memory on social

capital.The component of Political Interest is affected positively by age. Moreover,

similar to the findings of earlier studies, women are less interested in politics

than men (Borck, 2007), and better educated persons exhibit a significantly

Table 3

Rotated component matrix of social capital indicators

Factor 1 Factor 2 Factor 3 Factor 4

How interested are you in politics? 0.858 0.061 0.180 0.043How important in your life: politics? 0.838 0.096 0.024 0.019How often discuss politics with friends? 0.791 0.072 0.114 0.086How often spend time with friends? 0.032 0.780 0.071 0.096How important in your life: friends and

acquaintances0.130 0.715 0.004 0.048

How often spend time with colleagues? 0.040 0.619 0.235 0.051Sum Group membership 0.172 0.032 0.828 0.073How often spend time in clubs and voluntary

organizations?0.091 0.243 0.789 0.034

Sum Neighbors 0.022 0.006 0.105 0.838People can be trusted/Cannot be too careful 0.088 0.069 0.216 0.641

Dimension PoliticalInterest

FriendshipTies

AssociationActivity

Trust

Note:Grey background indicates which variable corresponds to which factor.

Table 4

Estimation for Equation (1) for total sample (with heteroscedasticity-consistent standard errors:White, 1980)

Political Interest Friendship Ties Assoc. Activity Trust

Coeff. Sig. Coeff. Sig. Coeff. Sig. Coeff. Sig.

(Constant) 0.987 0.000 1.408 0.000 0.454 0.001 0.653 0.000Age 0.022 0.001 0.060 0.000 0.014 0.026 0.021 0.002Age2 0.000 0.129 0.000 0.000 0.000 0.056 0.000 0.000Gender (1 = female) 0.310 0.000 0.139 0.000 0.164 0.000 0.065 0.054Education (level 1 8) 0.130 0.000 0.036 0.000 0.070 0.000 0.081 0.000Occupation 0.029 0.479 0.167 0.000 0.122 0.002 0.024 0.556Urban > 5,000 inhabitants 0.046 0.191 0.008 0.824 0.126 0.001 0.041 0.280Language: Italian =1 0.016 0.879 0.153 0.146 0.312 0.055 0.298 0.006Italy = 1 0.513 0.000 0.171 0.123 0.061 0.711 0.200 0.077

Bolzano = 1 0.730 0.000 0.708 0.000 0.639 0.000 0.734 0.000Trento = 1 0.449 0.000 0.329 0.000 0.541 0.000 0.023 0.748Tyrol = 1 0.061 0.321 0.429 0.000 0.247 0.000 0.179 0.003

R2 16.8% 18.8% 11.3% 7.9%

Note:Grey background indicates which variable are significant at the 10% level.




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greater interest in political affairs (Iyer et al., 2005). Interesting findings are

obtained for the variables for collective memory. Accordingly, the institutional

framework is important, as the inhabitants of Austria (including Tyrol) arepolitically more interested than are the citizens of overall Italy. The population of

Bolzano and Trento, however, shows a greater interest in politics than does the

population of Italy or Austria. No significant differences between the two lin-

guistic groups are found within the bilingual region Bolzano.

The findings concerning the impact factors of the component Friendship Ties

are similar. Friends/Colleagues are, however, more important for younger

people. Women and unemployed persons show a lower level of integration in

friendship networks. Higher levels of educational attainment are associated with

higher levels of friendship ties. Observing the influence of the regional propertiesindicates that neither the cultural proxy of language nor national affiliation

exhibits significant influences. However, all three regions investigated display a

significantly higher level of Friendship Ties than does Austria or Italy. Moreover,

the regions also vary among themselves in terms of Friendship Ties.

The third social capital factor, Association Activity, is one of the most

analyzed indicators of the quality of civil society. Highly significant coefficients

are obtained for the variables for gender, with women arguably still having less

time for associations due to family commitments, education, occupation and

degree of urbanization, and with people living in a town with more than 5,000inhabitants being less involved in associations. Again, no significant differences

between the two nations are found. Nevertheless, the Italian-speaking populace

is less active in associations than are the German-speaking people. The whole

investigation area Tyrol-Bolzano-Trento shows a higher level of Association

Activity than does Austria or Italy.

The dimension of social capital analyzed last is the particularly important

factor Generalized Trust, which is considered to be the main characteristic for

networks to become productive. Of the individual variables, age and education

are found to foster trust and women are reported to be significantly more trustingthan men. On a regional basis, the population of Tyrol is slightly less trusting

than is the rest of Austria. Bolzano exhibits a still lower level of trust. Within the

Province of Bolzano it is further possible to significantly differentiate the two

linguistic groups as the Italian-speaking population is somewhat more mistrust-

ing than is their German-speaking counterpart.

To provide a comprehensive picture of the impact of intra- and inter-regional

differences on social capital and the interaction of its components, the corre-

sponding values of the social capital factors are displayed graphically in Figure 2

for the groups Trento, German-speaking Bolzano, Italian-speaking Bolzano,Tyrol, and Italy (without Trento and Bolzano). Again, Austria without Tyrol is

not shown explicitly, because it serves as reference group and thus represents the

reference line at zero for all four analyzed components. The combined effect can




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be assessed by computing the expected value conditional on a change in the

variables Language and the dummies for Italy and the regions Bolzano, Trento

and Tyrol, while keeping all other variables constant:

E SC Language Italy Bolzano Trento Tyrol

b Language b

j

j j

, , , ,( )= + 7 8IItaly Bolzano Trento Tyrolb b b

j j j+ ++9 10 11

(2)

where

b b b b bj j j j j7 8 9 10 11, , , , estimations of equation (1) of social capital factorsSCj

Language linguistic affiliation (1 =German, 0 =Italian)

Italy living in Italy =1, 0 =otherwise

Bolzano living in Bolzano =1, 0 =otherwiseTrento living in Trento = 1, 0 =otherwise

Tyrol living in Tyrol =1, 0 =otherwise

These expected values for individuals in the entities and linguistic groups con-

trolling for individual factors and place of residence are graphically illustrated in

Figure 2. The corresponding findings will be discussed in the following section.

Both cultural groups in the bilingual Italian Province of Bolzano have a

significantly lower trust endowment than the other considered populationgroups.

Political Interest is significantly lower in Italy than in Austria. However,

Bolzano as a whole again shows distinctive values. Both linguistic groups

Figure 2

Illustration of expected values for individuals in the three regions and Italy and for linguistic

groups controlling for individual factors and place of residence, Austria is reference group.

-1.000

-0.800

-0.600

-0.400

-0.200

0.000

0.200

0.400

0.600

0.800

Political Interest Friendship Ties AssociationActivity

Generalized Trust

Italy

Bolzano - German

Bolzano - Italian

Trento

Tyrol




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show a higher value for Political Interest than does the rest of Italy, but also

higher than the two other subnational regions Trento and Tyrol.

Roughly the same can be said of Friendship Ties, which also permit asignificant differentiation between the German-speaking and the Italian-

speaking populations of Bolzano, with the latter relying more strongly on

friends.

Lastly, the German-speaking population of Bolzano has an outstanding level

of Association Activity as compared with the other analyzed population

groups.

In summary, the values for Trust are similar for Austria, Tyrol, Trento and Italy,

while the Province of Bolzano is significantly less trusting. A look at the threeother social capital dimensions, however, shows Italy to have the lowest levels

of Political Interest, Friendship Ties and Association Activity by comparison

with the other regions. Furthermore, Trento and Tyrol are found to be rather

similar in their endowment with social capital. Lastly, at least one or even both

linguistic groups in Bolzano show pronounced values for each of the social

capital factors.

VI. CONCLUSION

The stark differences in social capital observed between the inhabitants of

Bolzano and those of Trento and Tyrol are clear evidence for the lasting impact

of the shock and its imprint on collective memory. The similar social capital

values observed for Trento and Tyrol can possibly be interpreted as a cultural

effect of their long common history under Habsburg rule, even if that history was

not always a peaceful one. This common cultural experience, however, does not

apply to the Italian-speaking population of Bolzano, which immigrated from the

rest of Italy. Thus, the cultural effect within this sample is not related to the

linguistic affiliation, but rather to the historical experience of Habsburg rule.The other findings can be interpreted consistently in the framework of evo-

lutionary biology. A traumatic shock and the ensuing compulsory adaptation to

new conditions destroy General Trust and raise a groups alertness. The signifi-

cantly greater Political Interest noted in the population of Bolzano might thus be

an indication of such an increased awareness of the need to closely observe the

political environment for hints of possible influential changes in the social or

political structure. Furthermore, negative experiences inevitably evoke some

protective measures, such as the strengthening of ones group. Such a reaction

can be found for the two linguistic groups in Bolzano, both of which relyparticularly strongly on networks, such as friends (Italian-speaking population)

and associations (German-speaking population). This latter effect on the consid-

erable Association Activity of the German-speaking population of Bolzano may




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again be explained by historical facts. Fascism repressed the indigenous

German-speaking population mainly by banning its culture and traditions. Thus,

it seems likely that an oppressed population tries to secure its own norms, valuesand tradition by gathering together in associations to preserve its culture.

By contrast, the Italian-speaking population of Bolzano experienced not a

cultural shock but a migration shock. Therefore, associations as concentration

point for cultural facets do not have the same meaning for this Italian-speaking

populace, as immigrants from Northern Italy did not feel they had the same culture

as immigrants from Southern Italy. This drawback of missing common cultural

aspects of the Italian-speaking immigrants is thus seemingly overcome by focus-

ing more strongly on friends and colleagues. This assumption is supported by the

high level of Friendship Ties within the Italian-speaking population of Bolzano.Following this interpretation, it can be stated that individual-level as well as

systemic variables exert a significant influence on the various dimensions of

social capital. Furthermore, social capital might be influenced by a common

history, which in the current sample is apparently not determined by language

but rather by common historical experience under Habsburg rule. Lastly, par-

ticularly striking shocks are sustained in the collective memory of a society,

influencing its behavior for a rather long time (in the present case, for more than

90 years). Evidently, the means of protecting oneself from such shocks are not

transferable between the affected groups, but depend strongly on the type ofblow experienced.

The question whether this is truly the case or whether a method exists with

which the reactions of societies to such historical shocks can be systemized is left

to future research. Further samples for such additional analyses abound, as the

South Tyroleans are certainly not the only socio-ethnic group to have experi-

enced such negative shocks to their culture and traditions in the past or even

recent history.

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APPENDIX 1: SUMMARY STATISTICS FOR POPULATION AND

LABOUR MARKET IN THE THREE REGIONS

State of Tyrol Province of Bolzano Province of Trento

Sovereignty Austria Italy ItalyTotal populationa 706,873 503,434 524,826Area (km2) 12,647.71 7,400.43 6,206.88Official LanguagesGermanItalianLadin

100% 69.1%b

26.5%b

4.4%b

100%

Female inhabitantsa 51.1% 50.7% 51.1%Male inhabitantsa 48.9% 49.3% 48.9%GDP (Mio. EUR) 24,720b 17,269a 16,166.97a

GDP/per capita 35,200b 34,421a 30,950a

Labour forcea 373,600 244,200 237,595Employeda 362,900 237,200 229,254

Unemployeda 10,700 7,000 8,341Unemployment ratea 2.9% 2.9% 3.5%

Data source www.statistik.at www.provincia.bz.it www.statistica.provincia.tn.it

Year:a 2009b 2008

SUMMARY

The purpose of these analyses is to investigate collective memory, i.e. the shared historical experiences of a

community, as driving force for contemporary social capital. Three societal characteristics are considered

proxies for collective memory: the current institutional framework as indicator for present common experi-

ences; the cultural attitudes as proxy for long-term developments; and severe shocks in the history of the

regions. The primary aim is thus to understand whether collective memory permits identification of not only

the effects of recent (i.e. institutional) or distant (i.e. cultural) on-going experiences, but also of the impact

of such relevant shocks. For this purpose, a comprehensive case study is conducted within a cross-border

research area with special historical development, where it is possible to discriminate between these three

indicators of collective memory.

The findings suggest a significant impact of collective memory on social capital endowment. Particularly

striking shocks are sustained in the collective memory of a community, influencing its behavior even long

after the incident occurred. As a consequence, especially the levels of social trust and networking of the

affected population are significantly influenced, such that the community develops protective measures in

order to secure its norms, values and traditions. As a result, the social capital of a population is heavily

influenced by events that occurred outside living memory.



social capital and collective memory

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