ARCHIVED – Social Capital and Employment Entry of Recent Immigrants to Canada
2. Literature Review
During the last two decades, the concept of social capital has become a very popular term used across a number of disciplines of the social sciences. While it has been used in various ways, the definitions of social capital differ by field of study. In the literature on sociology and political science, social capital generally refers to networks of social relations which are characterized by norms of trust and reciprocity (Bourdieu, 1993; Putman, Leonardi and Nanetti, 1993) and which lead to outcomes of mutual benefit (Lochner et al. 1999; Stone et al. 2003). For instance, Coleman defined the classic concept that a social structure “facilitates certain actions of actors within the structure” (Coleman 1988, pp.98). The concept includes not only informal horizontal relationships and vertical hierarchical organizations, but it also formalizes institutional relationships and structures. In addition to this definition, economists emphasize the contribution of social capital to economic growth and performance, for individuals, communities and the aggregate economy (e.g. Chou 2006; Iyer, Kitson and Toh 2005). Some view it as economic relations embedded in a nexus of social activities, while some others see it as networks.
The reference to “capital” suggests that it is an economic good and not a natural given. Social capital must be constructed through investment and augmented by usage. However, while the term social capital has gained wide awareness, it has also been the object of much debate about its precise definition, especially among economists (e.g. Arrow 2000; Solow 2000). Actually, there is no consensus on this issue, but as pointed out by Durlauf (2002), the different underlying theories do not seem to oppose to each other.
Among the possible definitions of social capital, the one based on networks has been used widely in the socioeconomic literature (e.g. Montgomery 1991; Woolcock 2000; Rose 2000). In this way, measures of social capital are basically measures of networks. Bourdieu (1985) decomposes social capital into two elements: the social relationship itself, and its amount and quality. While there is considerable variation in network-based measurement, most approaches share Bourdieu’s view that measures of social capital must consider both the structure and the content of the networks. Stone (2001) provides a clear distinction between these two concepts. Structure includes size and density while content measures quality and trust within the structure. In this way, social capital can be thought as “structure multiplied by content” (Stone 2001). Furthermore, Stone, Gray and Hughes (2003) extend the analysis by providing multi-dimensional measures of social capital and by estimating the impact of both the structure and the quality of social networks. The present study will use a similar network-based concept and multi-dimensional measurement of social capital.
There has been a growing recognition among researchers using the term “social capital” that these social networks can have a lot of effects. Social capital or its key element – social networks – plays an important role in the labour market matching processes. Access to employment and mobility through career can be facilitated by social capital, although researchers do not always conceptualize it explicitly in that way. The role of social capital in the job market has been widely developed in the sociology literature (e.g. Lin 1999), but empirical applications are still limited. Moreover, due to conceptual difficulties in quantifying social capital and to limitations in social capital measures available in existing data, there are few economic studies on the effect of social capital on labour market outcomes.
The existing economic literature has analyzed mainly the theoretical effects of social relationships on labour force participation and job search processes within job matching models (e.g. Montgomery 1991; Cahuc and Fontaine 2002). Particular consideration has been given to problems related to workers’ mobility in terms of employment status and wage (Calvó-Armengol and Zenou 2005). According to these theoretical models, various types and patterns of social networks lead to better transitions from unemployment to work by reducing the cost of job search for potential employees and employers, and by producing a better quality of job match. Specifically, models have suggested that obtaining a job through networking is associated with higher acceptance rates of job offers (Holzer 1987), higher reported job satisfaction (Granovetter 1995) and lower quit rates (Datcher 1983), though not necessarily higher wages (Granovetter 1995) or new externalities (Fontaine 2003).
On the empirical side, studies have examined the efficiency of networking in terms of finding a job and the quality of jobs as mainly measured by the wage. Early work by Granovetter (1973) has pointed out that, while immediate social networks (relatives and close friends) do have an impact on job transitions, weak ties (distant relationships, e.g. workmates) dominate strong ties for both transitions and wages. In contrast, Montgomery (1992) shows that networking has a positive impact on employment transition, but this does not imply higher wages, even when weak ties are used.
In summary, the evidence suggests that social capital does affect labour market outcomes, especially job transitions. The role of social capital on employment status and earnings has been identified empirically as one of the driving forces of individual disparity in conjunction with human capital and external factors. However, there are substantial measurement differences in defining social networks and selection issues in interpreting the results of these studies, so the economic effects of social networks remain an open empirical question.
Social networks are expected to facilitate immigrants’ integration into their host countries. Recent research has indicated that higher levels of economic wellbeing are not themselves sufficient to lead to positive integration outcomes, but social capital, defined as social networks relating to both the structure and quality of social interactions, plays a critical role on the integration process of immigrants (Kunz 2005).
There is evidence that social capital influences immigrant economic performance significantly, especially in the initial years. Evidence from both Australia (Giorgas 2000) and the US (Amuedo-Dorantes and Mundra 2004) finds that ethnicity and social networking have served as a positive strategy for immigrants in general in their new labour market. Giorgas argues that social capital was used more effectively by groups with stronger cultural boundaries. Amuedo-Dorantes and Mundra find that social networks not only affect the likelihood of finding employment, but they also play an important role in facilitating the economic assimilation of Mexican immigrants in the US in terms of a higher hourly wage. In general, social networks provide a temporary shelter against unemployment for newcomers, and there are differences in social capital impact among groups of immigrants.
Most of the existing literature on the relationship between social capital and immigrant labour market outcomes is about the U.S. As data with information on employment, wage and detailed social network structure are relatively rare, most studies focus on a specific group of immigrants and use network-based job search methods as a proxy for social capital. For example, Livingston (2006) used the Mexican Migration Project (MMP) data to examine the effects of different network-based job searching. Munshi (2003) also made use of the MMP data to identify network effects among Mexican immigrants in the US labor market. He used variation within each origin-community’s network over time to examine network effects. Sanders, Nee and Sernau (2002) looked at how the reliance on interpersonal ties in job search affected Asian immigrants’ labour market outcomes in greater Los Angeles. Beaman (2007) paid special attention to the refugees resettled in the U.S., examining the linkage between the size of a social network, the employment status of network members and labour market outcomes.
In the context of Canada, despite the large immigrant population, little attention has yet been paid to the potential relationship between social networks and immigrant labour market performance. Again, probably due to the limitation of available data, existing Canadian researches are restricted to qualitative studies and case analyses focusing on small groups. For instance, Marger (2001) found that Canadian business immigrants had minimally relied on social capital in forms of ethnic networks and family ties to run their firms, based on a survey of 70 entrepreneurs in Ontario between 1993 and 1995. Bauder (2005) found that South Asian immigrants developed ethnic networks to overcome labour market barriers, while immigrants from the former Yugoslavia were reluctant to use personal ties as a job search channel.
Within the context of social network and immigrant labour market outcomes, a much-debated issue is the interpretation of high co-ethnic levels of social capital among immigrant groups. One influential argument is that family, friendship and neighbourhood ties (“bonding”) help people get by, while overlapping or diverse networks (“bridging” or “linking”) help people get better (Narayan 1999; Woolcock 2000; Stone, Gray and Hughes 2003). However, in the context of immigrant integration, there has not been much research so far showing whether a more heterogeneous social network is likely to result in a better outcome compared with a more homogeneous one.
A group of related studies lends some evidence on this issue by looking at ethnic or neighbourhood characteristics as a proxy for social capital. The effect of social networks on immigrants’ employment status and earnings may significantly differ according to how we define and measure them. For instance, employing home language as a proxy for social networks, Bertrand, Luttmer and Mullainathan (2000) uncover evidence that these social networks influence welfare participation in the United States. Chiswick and Miller (1996) measure social networks by the extent of linguistic concentration in the area where the immigrant resides in the U.S. They conclude that concentration of the home language has a negative effect on earnings. Borjas (1995) looks at one element of social capital, ethnic capital as measured by residential segregation of ethnic groups, and finds that ethnic neighbourhoods influence negatively the economic performance of immigrants in the US. Warman (2005) uses Borjas’ measurement of ethnicity – concentration of co-ethnic group in the neighbourhoods between 1990 and 2000 – to find a negative impact of enclaves based on country of birth on the ten-year wage growth of immigrants to Canada. While the results indicate a negative effect of enclaves on wage growth, little evidence is found of the effects of enclaves on changes in employment. Warman also points out that ethnic concentration has a divergent effect on different landing cohorts: a positive impact on the wage growth of the more recent cohorts and a negative impact on earlier cohorts.
It is also to be noticed that the immigrant labour market outcomes literature focuses mostly on earnings as the measurement of economic performance, with few studies applying the concept of social capital to employment probability. Considering the different measures of labour market outcomes and the disparity of definitions and measures of social networks, the role of social capital in the immigrant integration process remains unknown.
The LSIC Wave 1 has been employed to explore immigrants’ housing choices (Renaud, Bégin, Ferreira and Rose 2006) and inter-provincial migration (Mendez, Hiebert and Wyly 2006) without social networks included in the analyses. The social network effect has also received some attention in the area of intra-Canada migration (Houle, 2006). Houle used Wave 1 and 2 micro data of the LSIC to examine the internal migration behaviour of the LSIC immigrants in a survival analysis framework. He included several social network indicators in his analysis: presence and location of network upon landing; origin of new friends and participation in associations and found that geographic closeness determines immigrants’ intra-Canada migration significantly while other social network indicators show no significant effects. Although the structure elements of the networks were taken into account, the measurement was not specifically categorized according to types of networks. The present research is among the first to examine the network effects on immigrants’ labour market outcomes using the complete three waves of the LSIC.
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