سرمایه اجتماعی به عنوان شبکه های اجتماعی : چهارچوب جدید برای اندازه گیری و تجزیه و تحلیل تجربی عوامل تعیین کننده و پیامدهای آن

The contribution of this paper to the social capital literature is threefold. First, we set up a new framework for measurement, allowing us to build indicators for five different dimensions of the concept. Second, we provide a single, synthetic, measure capturing that particular configuration of social capital which the literature generally associates with positive economic outcomes. Third, we carry out an empirical assessment of the relationships between the different types of social capital identified by our analysis and a range of socio-economic phenomena.

The social capital literature suffers from two main problems. First, the definition of social capital remains elusive and, also due to the chronic lack of suitable data, there is neither an universal measurement method, nor a single underlying indicator commonly accepted by the literature. Second, given the assumption that social capital is a multidimensional concept, it is still unclear which dimension may exert a positive effect on the different aspects of development. Durlauf and Fafchamps (2006, p. 1642) argue that ‘social capital is not a concept but a praxis, a code word used to federate disparate but interrelated research interests and to facilitate the cross-fertilization of ideas across disciplinary boundaries’. As pointed out by Brown and Ashman (1996), one of the primary benefits of the idea of social capital is that it is allowing scholars, policy makers and practitioners from different disciplines to enjoy an unprecedent level of cooperation and dialogue. However, conceptual vagueness partly invalidates the credibility of empirical and theoretical studies on the possible effects of social capital. Measurement problems are rooted in the multidimensional and dynamic nature of the concept. Social capital in fact incorporates diverse phenomena such as culture, institutions, social norms, and networks of interpersonal relationships. As argued by Coleman (1988, p. 98), ‘Social capital is defined by its function … Like physical capital and human capital, it is not completely fungible, but may be specific to certain activities. A given form of social capital that is valuable in facilitating certain actions may be useless or even harmful for others’. The first aim of this paper is to draw a new framework for measurement, allowing us to build synthetic indicators of each social capital's dimension. Starting from the acknowledgement of the very multidimensionality of the concept, the analysis focuses exclusively on its “structural” components, which are here identified with social networks, that materialize themselves into measurable phenomena like relational goods’ consumption and social participation. However, as everyday-life experience suggests, social networks may play a double-sided role in development and well-being. According to their nature and scope, networks can in turn nurture or hamper social cohesion and the economic activity. The second aim of our study is to shed light on the socio-economic determinants and consequences of social capital, through an empirical investigation into the relationship between three types of networks, per capita income, the state of health of the environment, and the precariousness of employment. The choice of focusing on such variables in addition to an indicator of the economic performance is rooted in our discontent for the excessive attention devoted to growth by the literature. A growing number of studies states that, to be sustainable in the long run, growth must also preserve or improve the quality of life and of the environment, as well as lifelong learning processes and the stock of human capital possessed by the labour force (Easterly et al., 2006, Antoci et al., 2007 and Bartolini and Bonatti, 2008). It is our belief that the precariousness of employment plays a crucial role in determining social cohesion and the agents’ well-being. Precarious workers are generally characterized by low employment conditions in terms of pay, employment security, sickness and parental benefits, balance between work and private life. They are usually provided with less work-related training and enjoy scarce prospects of building a career. The high exposure to the risks of job loss, wage variability, and intermittent unemployment raises the uncertainty on future incomes, making difficult any form of long-term planning of life activities such as marriage and procreation. Labour precariousness can thus be seen as a barrier to social integration that may destroy human and social capital: a high level of flexibility on employment hinders training and qualification and, at the same time, hampers the consolidation of social ties, both inside and outside the workplace. While a stable and satisfactory work provides not only income, but also an identity and a ‘sense of belonging’, precariousness generates discouragement and distrust towards labour market institutions that, at the macro level, may result in a more distrustful society. The analysis in this paper is based on a dataset collected by the author including about 200 indicators of five main social capital dimensions: strong family ties (i.e. bonding social capital), weak informal ties (bridging social capital), voluntary organizations (linking social capital), active political participation and civic awareness. Rough data are drawn from a set of multipurpose surveys carried out by the Italian National Institute of Statistics (Istat) on a sample of 20,000 households between 1998 and 2002. The empirical investigation partly follows the strategy traced in Sabatini (2008). First, principal component analyses (PCAs) are performed on each of the five groups, in order to build a synthetic indicator measuring each social capital's dimension. Second, further PCAs are run on such indicators, in order to explore the structure of correlations between different dimensions and to test the popular claim that voluntary organizations foster the diffusion of civicness and cooperative values ( Putnam et al., 1993 and Brehm and Rahn, 1997). Third, a multiple factor analysis (MFA) is run on the entire dataset to the purposes of building a unique, synthetic, indicator representing that particular combination of social capital's different dimensions which the literature generally associates with positive socio-economic outcomes. The final stage of the analysis carries out an assessment of the determinants and consequences of social capital carried out by means of structural equations models (SEMs), a technique that has grown up in psychometrics and proves to be particularly suitable for the investigation of multidimensional phenomena. The outline of the paper is as follows: Section 2 introduces the concept of social capital and underlines its relevance to economics through a survey of the literature. Section 3 briefly reviews studies addressing the role of social capital in the labour market. Section 4 carries out a critical discussion of some measurement issues, pointing out the main weaknesses of the empirical studies in the field. Section 5 presents our method for the measurement of social capital and traces a map of its endowments in the Italian regions. The SEM analysis of the relationships between the three types of social capital, human development and labour precariousness is described in Section 6. The survey is closed by some concluding remarks and guidelines for further researches.

Overall, the empirical evidence in this paper allows us to distinguish between at least three types of networks. Strong family ties, corresponding to what the theoretical literature generally calls bonding social capital, strong and weak ties connecting friends, acquaintances and neighbours (bridging social capital), and weak ties connecting people belonging different socio-economic backgrounds within the activity of voluntary organizations (linking social capital). Such networks juxtapose each other in the Italian regions: Areas characterized by higher levels of bonding social capital can suffer from a lack of bridging and linking social capital. The analysis provides synthetic indicators for each type of network, that can be used as rough data in further econometric investigations, thereby proposing a new strategy for a systematic assessment of social capital's endowments, determinants, and consequences. Another useful tool for further econometric analyses is the “global indicator”, built by means of a MFA in Section 5.7, capturing that particular combination of the diverse social capital's dimensions which the literature generally associates with positive socio-economic outcomes. Higher levels of this particular measure indicate lower endowments of bonding social capital, a better quality of family relationships, more social participation and a higher involvement in community affairs. Other interesting findings of the multidimensional analysis can be summarized as follows. Interest in politics and public affairs is found to be negatively correlated with the bonding social capital shaped by strong family ties. On the contrary, the bridging social capital connected to relational goods’ consumption is generally accompanied by higher civic awareness and social participation. Active political participation through parties is not correlated to civic participation through voluntary organizations, but exhibits an interesting positive relationship with bonding social capital. Southern regions like Molise, Calabria and Puglia are characterized by high levels of people involvement in political parties life which, however, do not correspond to a diffuse interest in politics and public affairs. This trend can be attributed to the fact that, in Southern Italy, political militancy is often considered as a mean to pursue narrow, sectarian, interests and to obtain patronage favours, rather than a way to participate in collective affairs. Higher levels of religious participation are strongly correlated with the presence of bonding social capital and with a scarce interest in politics and civic affairs, while bridging and linking ties show a significant correlation with a low religious participation. This may confirm Putnam's (1995) interpretation of the catholic church as a particular form of bonding social capital, which do not create mutuality and equality of participation, and do not have the same effect as membership in social capital-rich groups. The SEM analysis carried out in Section 6 shows that the literature generally underestimates the positive role exerted on well-being by the mutual assistance and social protection mechanisms promoted by the family. Through their ability to mitigate precariousness, strong family ties may act as a means of defence against high levels of unemployment. In other words, bonding social capital can be seen not only as a cause of backwardness, but also as one of its possible consequences. The widespread idea that social contacts function as a powerful job placement factor is only partly confirmed by data. In Italy, just strong ties support the reduction of precariousness, while weak ties connecting friends and acquaintances seem not to be helpful to such purposes. What certainly deserves further investigations is the effect of social networks-induced job matching processes on the allocation of talents: significant mismatches of talents and an excessive job market's closure to outsiders may cause a reduction of efficiency compensating the beneficial effects of precariousness’ alleviation. Anyway, it is clear that neglecting the social embeddedness of actors seriously invalidates the explanatory power of any economic analysis of the labour market. Voluntary organizations are the only type of networks that are positively correlated with the economic performance. In Italy, the associational activity is strictly connected to sound ideological motivations, and generally implies the sharing of moral norms of trust and reciprocity that can counteract the negative effects of the ‘amoral familism’, as well as the tendency of organizations to lobby for the narrow interests of their members.