Cross-National Patterns of Social Capital Accumulation

Abstract

Cultural and institutional context has the potential to moderate life course patterns of social interaction and network connectivity, yet few have attempted to empirically assess this claim. Contrasting collectivist versus individualistic cultural traditions, as well as socialist versus capitalist institutions, we develop and test a set of propositions regarding age-based variation in daily contact, occupational connections, and organizational memberships in China, Taiwan, and the United States. Analyses from cross-sectional survey data reveal how the cultural and institutional differences help structure access to social capital across age. Specifically, the data show how social capital accumulation in the individualistic societies is facilitated by employment and civic institutions, whereas family institutions form the basis for social capital accumulation in collectivist societies.

Keywords

social capital social networks life course aging Asian societies

In navigating lifetime experiences, transitions, and pathways, people rely on a set of resources termed “life course capitals”—including human, social, health, and personal capitals (O’Rand, 2006)—all of which contribute to wealth, well-being, and mortality. Identifying unique age-based trajectories of these life course capitals can therefore assist in explaining social inequality (McDonald & Mair, 2010). The long-term patterns of accumulation, maintenance, and erosion of these resources as individuals’ age can uncover processes of cumulative advantage/disadvantage (DiPrete & Eirich, 2006). Furthermore, exploring these patterns in cross-national contexts can help explain the ways in which distinct institutional arrangements, cultural repertoires, and historical contingencies influence social stratification.

Although age variation in some of the life course capitals has been examined extensively (e.g., Chen, Yang, & Liu, 2010; Willson, Shuey, & Elder, 2007), relatively few studies examined age-based patterns of social capital. Instead, the majority of the work on the dynamics of social capital focused on historical shifts in social capital (McPherson, Smith-Lovin, & Brashears, 2006; Paxton, 1999; Putnam, 2000). Studies that have reported on age variation in social resources tend to focus on narrowly defined age ranges (Cornwell, Laumann, & Schumm, 2008; Kalmijn, 2003; Wellman, Wong, Tindall, & Nazer, 1997). While recent research has begun to incorporate broader age ranges into analyses of social capital accumulation (Cornwell, 2011; Kalmijn, 2012; McDonald & Mair, 2010; Schwadel & Stout, 2012), the role that social institutions play in shaping these life course patterns remains uncertain.

The present study addresses this gap in understanding by considering how age variation in access to social capital resources may vary across multiple societies. Earlier studies have shown that transitions in institutional arrangements can have a profound impact on the character of social ties (Gerber & Mayorova, 2010; Ruan, Freeman, Dai, Pan, & Zhang, 1997; Yakubovich & Kozina, 2000). As such, one should expect the accumulation of social resources to vary substantially across different institutional fields. Using data from a unique comparative survey data source—the Social Capital Survey, 2005—we compare the age-based patterns of daily interpersonal contact, occupational network connections, kin-based ties, and voluntary association memberships in the China, Taiwan, and the United States. These three societies are useful to compare because they represent distinct cultural and institutional contexts, providing interesting test cases for understanding how the presence of different forms of social capital vary across age and society.

Cross-Society Differences

Cultural and political/economic differences across nations at the macro-level shape meso-level social practices, such as the accumulation of social capital ties, through a range of specific mechanisms. National culture likely operates through normative preferences for interaction (e.g., desired ties, availability of ties, and normative use of ties), whereas national political/economic factors likely operate through structural availability of ties. These national patterns can translate into different social network compositions cross-nationally and across age.

China and Taiwan are steeped in the Confucian tradition that is characterized by a high degree of collectivism and emphasizes the importance of interpersonal, especially family, relationships (Inglehart & Baker, 2000; Son, 2013). Confucianism also maintains strict social hierarchies that are strongly linked to age and gender, with older males holding positions of greatest reverence and authority (Bian & Ikeda, 2014). Confucian traditions have also influenced social interaction through guanxi, which is a form of social exchange that favors strong tie connections often facilitated by kin relations (Bian & Ang, 1997). Conversely, the United States is known for its emphasis on individualism, which promotes a “go-it-alone” approach to succeeding in life (Hochschild, 1995). The United States has also had a long tradition of community and civic participation (Tocqueville, 1835/1961). The civic mindedness implies an openness of participation in civil society, enhanced by the development of ties to individuals who are connected to social and economic organizations. Protestant religious beliefs and democratic institutions have been linked to a high degree of participation in voluntary organization memberships in other advanced countries as well (Curtis, Baer, & Grabb, 2001).

China’s socialist institutional tradition is distinct from the United States and Taiwan. Despite the recent economic reforms and shift toward greater economic development, the legacy of authoritarian and communist institutional control remains strong in modern China. Economic and social development are still highly coordinated by the government. By contrast, the United States and Taiwan have far more liberalized economic and political institutions. Deregulated markets have long been the standard in the United States, but Taiwan also maintains a robust set of capitalist institutions and impressive capitalist growth the 1960s and into the 2000s (Hsu & Cheng, 2002; Lee, 2008). In addition, socialist nations tend to have more generous retirement plans and younger work forces (U.S. Census Bureau, 2005; U.S. Social Security Administration, 1979-2008). Therefore, compared with socialist nations (e.g., China), capitalist nations (e.g., the United States) are more likely to work longer at older ages.

Based on these cultural and institutional differences, we offer a set of predictions (summarized in Figure 1) for how social capital should vary overall and across age in these three societies. The emphasis on interpersonal relationships apparent in the Confucian tradition within China and Taiwan is likely to lead to more daily social interaction than what is found in the more individualistic U.S. People in the United States and in Taiwan should have the most expansive occupational networks due to the predominance of market principles and the lack of constraints on occupational mobility relative to China. Due to the Confucian tradition, the occupational networks in China and Taiwan should contain greater numbers of strong ties and kin-based relationships than what one might expect to find in U.S. networks, which should contain more weak and nonkin ties. The openness and civicness of the Western capitalist experience within the United States are likely to influence networks in the opposite direction: less interaction, broader networks, and weaker ties, as well as increased participation in voluntary associations. By contrast, the lack of exposure to democratic institutions and the absence of Protestant cultural values in Asian societies should render voluntary association memberships less salient than in the United States.

Figure 1.

Predicted differences in network resources across societies and age.

Our cultural and institutional typology is also suggestive of age-based differences in social capital. Prior research has established that social interaction tends to decline with age in North America (Carstensen, 1995; Kalmijn, 2003; Schwadel & Stout, 2012; Wellman et al., 1997). Because of the prominence afforded to older individuals within Confucian societies, we predict that the decline in daily connections across age should not be as steep in China and Taiwan. In fact, daily connections may even increase with age in Asian societies. In established liberal market economies, workers generally display a pattern of accumulation of work-based connections across their working lives, with a slight decline in occupational connections at the end of their working careers (Erickson, 2003; McDonald & Mair, 2010). So while we expect to see this accumulative pattern in the United States and to a lesser extent in Taiwan, we predict a modest decline in the extent of occupational connections across careers in China. Whereas interoccupational mobility is quite common across careers for U.S. workers, Chinese workers display less variability in mobility patterns which could lead to a modest narrowing in occupational connections as careers progress. In the United States, educational institutions offer broad skills and limited connections to employment (Kerckhoff, 2003; Shanahan, Mortimer, & Kruger, 2002). Consequently, U.S. workers are likely to rely on family-based networks in order to enter their careers. The prominence and efficacy of these strong kin-based ties is likely to decline as workers accumulate greater work experience and work-based connections. By contrast, family contacts are likely to remain in significant numbers throughout work careers in China, due to the strong reliance on family relations apparent in Confucianism. Finally, memberships in voluntary organizations are integral to the careers of American workers (Rotolo & Wilson, 2003), which leads us to suspect that participation in these organizations will increase with age. Voluntary organizations play a relatively minor role in China and Taiwan; we therefore predict stable and few organizational memberships across the age continuum in these two countries.

Data and Method

“Social Capital: Its Origins and Consequences” is a telephone survey of residents in three societies (the United States, China, and Taiwan) conducted from November 2004 to March 2005. The U.S. and Taiwanese samples are based on national random-digit dialing procedures. In China, random telephone sampling was conducted within the major cities and surrounding areas of 22 provinces and 5 autonomous regions. Respondents were eligible if they were between the ages of 21 and 64 years and worked for pay at some point in their lives. A total of at least 3,000 survey respondents were interviewed within each of the three societies.

Table 1 reports the descriptive statistics and describes the variables used in the analyses. First, the survey asked about the number of people with whom each respondent made contact during a typical day, with response categories ranging from 0 to 4 people (Category 1) to more than 100 (Category 6). This variable was recoded to the category midpoints for ease of interpretation. This question has been shown to tap into both instrumental and expressive aspects of social capital (Fu, 2005).

Table 1.

Descriptive Statistics for Key Variables.

Variable	Description		China (N = 3,414)		Taiwan (N = 3,132)		United States (N = 2,924)
Daily contact	“On average, about how many people do you make contact with in a typical day?” 6 categories, recoded to midpoints.	M	26.70	b, c	34.94	a, c	36.86	a, b
		SD	27.39		34.93		37.98
		Range	2-125		2-125		2-125
Occupational contacts	“Is there anyone you know who is a . . . ?” List of 21 different occupations.	M	7.18	b	8.63	a, c	7.25	b
		SD	4.47		5.16		3.87
		Range	1-21		1-21		1-21
Proportion close kin contacts	Proportion of the total number of occupational contacts who are relatives and perceived by respondents to be close.	M	0.20	c	0.20	c	0.23	a, b
		SD	0.23		0.24		0.24
		Range	0-1		0-1		0-1
Organization membership	Number of voluntary organizations that respondents report being members of. List of 10 different organizations.	M	0.16	b, c	0.64	a, c	1.94	a, b
		SD	0.55		0.85		1.66
		Range	0-5		0-5		0-5
Age	Measured in years.	M	38.36		40.70		41.58
		SD	10.27		11.59		10.49
		Range	21-64		21-64		21-64

Note. Two-tailed t test for difference of means: significantly different (p < .05) from (a) China, (b) Taiwan, (c) United States. t Tests conducted only for social capital variables.

The occupational networks of respondents were measured by a set of position generator questions. Respondents were provided with a list of 21 different occupations and asked if they knew someone within each occupation. The list covered a wide range of occupations, from janitors to CEOs. The outcome of interest is the total number of occupations for which respondents had a contact. This measure has been referred to in the past as extensity and serves as a measure of the diversity of occupational connections. Lin, Fu, and Hsung (2001) have noted the importance of this measure, as it serves as an indicator of the breadth of social connections that can be useful for job mobility.

When a respondent said that they knew someone in an occupation, they were asked to provide more information about that person—if they knew more than one person, respondents were instructed to report on the person that they knew the best.¹ These “name interpreter” questions were used to determine the relationship between alters and respondents. Strong kin ties are indicated by alters who are related to the respondent and are deemed to be either “close” or “very close” relationships. The strong kin ties are summed and then divided by the total number of occupational connections to obtain a sense of the strong-tie composition of occupational network.

Finally, respondents were offered a list of organizations to which respondents might belong. These include memberships in political, professional, religious, leisure/sports/cultural, and neighborhood organizations. The U.S. and China samples were asked more exhaustive lists of organizations (10 and 11 organizations) compared with Taiwan (5). Therefore, all membership counts were top-coded at 5. We were initially concerned that this could lead to an underestimation of the count for Taiwan. However, only three individuals from the Taiwan sample indicated membership in more than 4 organizations, so it seems unlikely that the distribution would have changed dramatically if more response options were available. Likewise, top-coding resulted in no change in the mean or standard deviation values for China (no respondent claimed more than 6 memberships, despite the option of up to 11) and only resulted in minor reductions in the mean (from 2.03 to 1.94) and standard deviation (from 1.87 to 1.66) for the U.S. sample due to the strong positive skew. Consequently, we are confident that the recoded estimates reflect a good approximation of the extent of organization memberships across these societies.

We conduct two tests to evaluate our predictions. First, we examine the overall differences in the social capital variables across the three societies by comparing the values for these variables using independent sample t tests (see Table 1). Second, we plotted age variation in social capital across the three societies in Figures 2 through 5. These estimates show the predicted values on the social capital variables based on ordinary least squares regression. The regression models include linear and squared terms for age, both of which are interacted with country-specific dummy variables to show the variation across societies. The models also include a set of control variables (see the appendix) to account for compositional differences across the three samples. These control variables include personal (minority status, education, self-rated health), residential (urban/rural status, duration at residence), family (marital status, marital duration, number of children), and employment characteristics (employment status, salary, supervisory status, firm size).

Figure 2.

Age variation in daily contact.

Figure 3.

Age variation in nonwork-related daily contact.

Figure 4.

Age variation in occupational contacts.

Figure 5.

Age variation in proportion of close kin occupational contacts.

Results

To begin with, the U.S. sample reports the highest average daily contact and China with the lowest, with Taiwan in the middle. This is the opposite of our expectations, as we anticipated that collectivist cultural orientation would result in higher levels of daily interaction among the Asian societies. How might one explain this finding? It is important to recall that the daily contact variable is a measure of the number of people with whom respondents interact in a normal day. Consequently, it might be that Chinese individuals engage in more overall discussions but with fewer alters than what is observed in the United States. Chinese guanxi highly values the cultivation of extensive web of indirect connections, but this practice does not appear to translate into a high volume of daily contacts. Unfortunately, our data do not allow us to test this idea.

The higher levels of daily contact in the United States and Taiwan could also be related to greater salience of work-based conversations. Interpersonal communication networks in advanced capitalist societies are increasingly dominated by work-related issues (Habermas, 1987). We can explore this issue via a question on the Social Capital Survey which asked employed respondents² to report on the amount of their daily contact that was related to work: all, most, half, few, and none. Chinese respondents reported the lowest proportion of work related daily contact. After reversing the categories and converting them to proportions (1, .75, .5, .25, 0), we multiplied them by the number of total daily contact to obtain estimates of the total nonwork daily contact. Chinese workers have significantly more nonwork daily contacts than U.S. workers, although Taiwanese workers have the most total nonwork daily contacts of the three societies. Consequently, a lack of work-related contact does help partially explain the low levels of daily contact among the Chinese.

Figure 2 displays the age variability in daily contact across the three societies. The solid lines show the average number of daily contacts at each age across the three societies. The dashed lines show the confidence intervals around those average estimates. The patterns are all similar in that they show a general decline in the extent of daily contact with age, especially during early-mid adulthood. Chinese respondents have a substantial increase in daily contact starting around age 40 years. We also explored the age variation in nonwork daily contact (see Figure 3). These patterns are quite distinct for the three societies. Nonwork contacts tend to decline with age for U.S. workers, increase with age for Chinese workers, and decline slightly across age for Taiwanese workers. This suggests (a) that the overall decline in daily contact in the United States (see Figure 2) is mainly due to a loss of nonwork contacts (see Figure 3); (b) that the uptick in daily contact among older Chinese respondents is aided by the increase in nonwork connections; and (c) that the decline in daily contact in Taiwan includes a loss of both work and nonwork contacts.

Returning to Table 1, the results show that individuals in Taiwan maintain a significant advantage in the number of occupations in which they know someone. On average, they report knowing people in nearly 9 out of 21 occupations, compared with a little over 7 for China and the United States. The relatively low number of occupational connections in the United States seems particularly surprising. When looking at the age-based relationship with occupational connections (see Figure 4), one observes three very distinct patterns. In the United States, occupational connections accumulate with age, whereas they decline slightly with age in China. Interestingly, Taiwan exhibits both features—a steep rise in occupational connections during the first portion of life and a steep decline later in life. This curve from Taiwan may be due to a cohort effect, whereby the age-based contact curve for younger workers looks more like that of U.S. workers because they have experienced the full impact of growth from capitalist economic institutions, whereas older Taiwanese workers have not and therefore display occupational connections similar to those of older Chinese workers.

The results from Table 1 also reveal that respondents from the U.S. sample, relative to those in China and Taiwan, maintain a significantly higher proportion of occupational contacts who are both kin and close ties. This finding seems counterintuitive considering our expressed expectations of greater kin connections in the Asian societies. However, the age-based patterns of these close kin ties help explain these differences (see Figure 5). The advantage in proportion of close kin connections among Americans is confined to the early part of careers. Informal job finding is common in the United States during the early portion of careers (McDonald, 2005) and much of this involves a reliance on kin connections. As U.S. workers gain more experience and become more embedded within their careers, their occupational connections become increasingly filled with nonkin and weak ties. By contrast, the proportion of close kin ties tends to increase with age for people in China and Taiwan. Only during the late career period (age 50+ years) does the relationship between age and close kin connections move in tandem for all three societies.

The voluntary organization membership results are highly consistent with our predictions. Overall, respondents in the U.S. report being members in significantly more organizations than respondents in either Taiwan or in China (see Table 1). People in Taiwan also participate in more organizations than Chinese. Examining the age-based patterns of organizational memberships (see Figure 6), the U.S. respondents show an accumulative pattern of membership participation across age. Despite their relatively low levels of organizational memberships, Taiwanese workers display a similar age-based accumulation of organizational memberships, along with a similar leveling of those connections in the late career period. By contrast, the relationship between age and organizational memberships is mostly flat in China.

Figure 6.

Age variation in organizational memberships.

Discussion and Implications

This study is an attempt to link patterns of life course variation in social capital with macro-level characteristics: culture and political economy. The results offer insights into the ways that context influences the accumulation and/or decline social capital in a progression of life course. Some of the findings were surprising. The differences across the societies in the overall levels of social interaction tended to counter expectations, whereas the age-based predictions regarding social capital variation were mostly supported. Overall, the results suggest that the accumulation of social capital is linked to employment and civic institutions in individualistic societies and to family institutions in collectivist societies. We elaborate on these findings below.

Despite expecting to see more daily connections with network alters in Confucian societies than in the individualistic United States, we actually observed the reverse. Our supplementary analyses revealed that this difference was at least partly explained by the fact that work-based daily contact is more prevalent in the United States than in China. Focusing on nonwork contact alone gives the daily contact advantage to China over the United States (but not Taiwan). One might observe a more prominent daily contact advantage in favor of China if the variable was measured as the frequency of interaction rather than the number of people with whom respondents interacted.

Alternatively, the greater social interaction in the United States could be due to the increased openness of American society. Chinese society is historically characterized by a rigid social stratification reinforced by Confucian teaching (Bian, 2002). The national college entrance examination (often seen as an extension of the traditional Chinese Imperial exam system) has arguably reinforced the hierarchical social relationship and strict social order (Zhou, 2004). As a result, the amount of daily contact in China may be less than the United States because of class boundaries. Moreover, the more extensive daily interaction observed in the United States could also be linked to a stronger culture of networking that has emerged as a critical tool for social mobility (see, e.g., Turner, 1960). These possibilities deserve further consideration in future studies of cross-society differences in social capital.

The age-based patterns of daily contact conform to expectations in that we observe a general decline in daily interaction with age among Americans, but an increase in daily interaction in China starting at age 40 years. This increase in daily contact among older Chinese respondents is especially pronounced for nonwork-related daily contact. Overall, these findings are consistent with the notion that the increased social status afforded to older individuals in China should lead to more rather than less social interaction among the aged.

We observed a significantly greater number of occupational contacts among Taiwanese respondents, which is difficult to explain via cultural/institutional differences. We speculate that the high levels of population density among people living in Taiwan (644 per square kilometer) relative to the United States and China (32 and 141, respectively), might afford Taiwanese individuals greater opportunity to know people in a broader array of different occupations (Population Reference Bureau, 2011). The relatively high proportion of close kin relations in the occupational networks of U.S. respondents also did not match expectations. However, the age-based patterns of occupational connections help explain why these differences have emerged. Specifically, the results reveal a distinctive age structuring of overall and close kin work connections in the United States During the early portion of careers in the United States, the work-relevant and occupational networks tend to be small and focused on close kin relations. This reality likely reflects the fact that U.S. educational institutions do a relatively poor job of integrating youth into employment settings (Kerckhoff, 2003; Shanahan et al., 2002). While others have noted the mismatch between educational training and employment skills (e.g., Bills, 2003), the low levels of weak occupational connections among early career U.S. workers may point to a lack of social integration into occupational careers as well. While much human capital accumulation occurs in the United States, so too does it appear that much of the social capital accumulation occurs via work experience (McDonald, 2011). Taiwan exhibits a similar (albeit much steeper) pattern of accumulation of occupational connections during the early portion of careers. This suggests that the adoption of capitalist economic institutions may be leading to similar age structuring of work-based connections, despite a very different starting point for access to occupational ties early in the career.

The results for organizational memberships are highly consistent with expectations regarding overall levels and life course variation. Voluntary associations play a much more dominant role in U.S. civil society than in Taiwan and least of all in China. As expected, the number of organizational memberships tends to increase with age in the United States and we have observed a similar pattern among respondents in Taiwan, despite lower overall totals. In China, the average number of organizational memberships remains quite low across all ages. Consequently, volunteering likely means something quite different in the United States than in China, as U.S. workers may use volunteer/organizational memberships more for occupational gain, whereas volunteering in China may take on more of a community-building/charity role. This is an important area for further exploration.

Overall, this study is useful because it helps illuminate the ways that cultural practices and institutional arrangements help structure access to and opportunities for social interaction. The findings reveal that these opportunities are linked to age-based patterns of social capital accumulation and decline—patterns that might otherwise be obscured by a singular focus on mean differences across societies. The study of the intersection of age and social capital shows how the individualistic and capitalist model in the United States facilitates access to social capital through the public sphere (employment and civic life), whereas the Confucian and socialist model in China affords social capital via the private sphere (family). In most instances (occupational contacts being the primary exception), Taiwan falls somewhere in between these two extremes. Its respondents maintain some patterns that mimic the West (i.e., daily contact and organizational memberships) and some that mimic the East (i.e., close kin ties). Further Westernization and marketization of its culture and institutions will likely bring these age-based patterns of social interaction increasingly in line with those of the United States.

Of course, one should take care not to extend these conclusions too far. Further research is needed to explore different measurement strategies to assess the robustness of the findings presented here. Also, while this study has explicitly emphasized the ways that access to social capital is influenced by aging processes, cohort and period effects are also likely to play a role in explaining the age-based curves presented here. We do not have space in this article for a full treatment of these issues, but encourage others to explore these issues to generate further understanding of how cultural and institutional transformations influence access to life course social capital.

Footnotes

Appendix

Descriptive Statistics for Independent Variables. (N = 9,470).

	M	SD	Min	Max
Race/ethnic minority	0.19	0.39	0	1
Highest degree	4.50	1.36	1	7
Health	3.47	0.86	1	4
Urbanicity	3.80	1.12	1	5
Years since last move (logged)	2.89	0.96	0	4.17
Married or cohabiting	0.73	0.44	0	1
Marital duration (logged)	1.92	1.34	0	3.95
Number of people in household	3.62	1.67	1	10
Number of children	1.48	1.24	0	5
Unemployed	0.23	0.42	0	1
Annual salary (logged)	7.53	4.30	0	12.69
Supervisor	0.48	0.72	0	2
Firm size	1.84	1.40	0	4

Acknowledgements

We are appreciative for helpful feedback received from Chris Marcum and Ben Cornwell.

Authors’ Note

An earlier version of this article was presented at the 2012 Population Association of America annual meeting.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Data cited here were collected in the thematic research project, “Social Capital: Its Origins and Consequences” (Grant No: AS-94-TP-Co2; Grant Period: 2004-2007), funded by Academia Sinica. The principal investigators were Nan Lin, Yang-chih Fu, and Chih-jou Jay Chen.

Notes

Author Biographies

Steve McDonald is an associate professor of sociology at North Carolina State University. He has published over 30 research articles and book chapters examining social networks and race, class, and gender inequality in labor markets.

Feinian Chen is a professor of sociology and faculty associate of Maryland Population Research Center at University of Maryland, College Park. Her primary research interests are intergenerational relationships and their implications for health and aging processes in transitional societies.

Christine A. Mair is an assistant professor of sociology at the University of Maryland, Baltimore County. Her research explores social ties and well-being across the life course in various local and national contexts.

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