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A typology of social capital and associated network measures

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Abstract

I provide a typology of social capital, breaking it down into seven more fundamental forms of capital: information capital, brokerage capital, coordination and leadership capital, bridging capital, favor capital, reputation capital, and community capital. I discuss how most of these forms of social capital can be identified using different network-based measures.

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Notes

  1. For instance, see the discussion in Knack and Keefer (1997), Jackson (2019b).

  2. One can find earlier mentions of the term—going back to the late 1800s—but often with different meanings from the more modern ones.

  3. See, for instance, the many definitions in Portes (1998), Woolcock (1998), Dasgupta and Serageldin (2001), Sobel (2002), Glaeser et al. (2002), Dasgupta (2005). That important forms of capital are embodied in humans as well as their relationships is even mentioned in the writings of Alfred Marshall.

  4. Marshall’s views were complex and changed over time, e.g., see the discussion of Blandy (1967).

  5. The exclusion of land and labor as forms of capital is mainly made to stick with the historical distinction. That historical distinction was made mostly for convenience—it can be very useful to distinguish capital and labor in estimating production functions and in many modeling and policy applications. Given that land and labor play no role in the discussion here, I exclude them for ease of exposition and to stick with the classical roots of the definition, but not for some deeper logical reason.

  6. Here I also separate distribution from production, just so that people understand that it is included, although one could fold it into the definition of production if that term is suitably understood.

  7. This is also another source of confusion in the use of the term ‘social capital’, as it is often invoked in contexts relative to the improvement of an individual, which is certainly part of the story, but without reference to any production. Ultimately we care about how capital is instrumental in the “production” of something—a good, service, entertainment, or anything else that can be consumed or enjoyed by someone. Thus, something like favor capital can be possessed by an individual, but the value comes from the productive uses that it can eventually enable.

  8. Note that some uses could also have negative value, for instance some forms of favor capital might include nepotism that has negative externalities. But many forms of production involve externalities, and that does not change the discussion of whether something is an essential and valued input to that production process.

  9. Network measures of centrality, influence, and power are abundant (e.g., see Borgatti 2005; Jackson 2008; Bloch et al. 2016; Jackson 2019b). Although there is much discussion of centrality measures in the literature, the explicit discussion of how different ones may be used to identify different forms of social capital is new to this paper.

  10. See also Lin (1999), Flap and Völker (2001), Kawachi et al. (2004), and Aldrich (2012).

  11. Generally, I will consider a case in which \(g_{ii}=0\), so that there are no self-loops, but this is not consequential to the formal definitions.

  12. For example, Arrow and Borzekowski (2004) discuss how having more access to job information can result in more productive matching between workers and jobs.

  13. See Jackson et al. (2018). For another reason for such a decay, see Manea (2017) who examines a model of resale of information with bargaining.

  14. See also the related notion of cascade centrality from Kempe et al. (2003, 2005).

  15. Communication and diffusion centrality allow for heterogeneous weightings, while decay centrality does not. However, it similarly extends by tracking shortest weighted paths.

  16. For instance, see Atkeson and Kehoe (1993) who consider the impact of the knowledge embodied in a group or organization.

  17. See Katz (1953), Bonacich (1987), Jackson (2008), Laguna-Müggenburg (2017) for discussion. Laguna-Müggenburg (2017) shows that including values can make a big difference in who is most central, especially in networks with homophily.

  18. This requires that the entries of \({\mathbf {p}}\) be substantially lower than one over the average degree, so that closer neighborhoods are accounting for relatively more of the calculations. More generally.

  19. If one has an estimate for clustering, then one could further refine the estimate by adjusting this to account for the fact that some of those node’s friends may already be in i’s second neighborhood. So if average clustering is \({\overline{c}}\), then the estimation of nodes at distance 3 would be \( p^2 n_i^2 ({\overline{d}}-1)-2 {\overline{c}} \frac{n_i^2 (n_i^2-1)}{2}\), where the last expression accounts for the fact that if two nodes at distance two are connected to each other, then we should lower the count of further friends that we attribute to each of them by one (hence the factor 2). One could make further adjustments to account for the number of friends that nodes at distance 2 have that are at distance 1: that is if there are several paths of length 2 from i to some j, then several of j’s friends have already been counted.

  20. An even better approximation is to adjust the \({\overline{d}}\) to be the average degree of neighbors in the network, which is generally higher than the average degree (e.g., see Jackson 2019a). An approximation is \(E[d^2]/{\overline{d}}\).

  21. In that case, clustering and double counting is less of an issue, since all walks are counted, and so the approximations are even easier.

  22. This is a very narrow use of the term leadership, as it stems entirely from a person’s positional ability to coordinate the activity of others, but does not involve other personal characteristics or other factors that determines whether people will actually pay attention to the individual.

  23. See the discussion in Kent (1978), Padgett and Ansell (1993), Jackson (2008, 2019b).

  24. For example, see the discussion in Brass and Krackhardt (1999) of the importance of network position and coordination in leadership. Being able to coordinate others has also been discussed in defining power (e.g., see Pfeffer 1981, 1992), as well as how unequal allocations can be (Kets et al. 2011).

  25. For a discussion of truncated betweenness centrality measures to address this concern, see Ercsey-Ravasz et al. (2012).

  26. One way to account for these issues is weight paths by their length. For instance, for some decreasing function \(f(\ell )\), \(\sum _{(j,k): j\ne i \ne k \ne j } f(\ell _{{\mathbf {g}}}(j,k) )\frac{\nu _{{\mathbf {g}}}(i:j,k)}{\nu _{{\mathbf {g}}}(j,k)}.\)

  27. This differs from the sorts of measures that one finds in some network software, e.g. UCINET, which calculate measures based on group assignments and directed interactions. (For more discussion behind those measures see Gould and Fernandez 1989.) Those are actually closer in spirit, but still different from, what is proposed to measure bridging capital below.

  28. This brings up a refinement of the measure of brokerage capital in cases where markets are bilateral. In the first example of countries, it could be that any two countries could need to enter negotiation and so the Godfather index properly captures the potential interactions. In an example of serving as an agent between buyers and sellers, then in counting the Godfather index, one would want to only count pairs of neighbors that involve one buyer and one seller, but discard pairs that involve two sellers or two buyers. That is, being a unique connector between two sellers might be useless since they do not need to transact.

  29. Bridging capital is perhaps conceptually the most closely related to Burt’s (1992, 2000, 2005) notion of structural holes, although his discussions include aspects of all three of bridging, brokerage, and coordination capital.

  30. See also Anderson (2017) for an account of how particular combinations of skills and knowledge can be more valuable than separate skills or superficial knowledge of many skills.

  31. This is a much more direct measure than something like the effective size of Burt (1992), which does not capture exclusivity. Effective size computes a node’s degree and then subtracts the average degree of that node’s friends. Having many friends who are not well connected themselves may be correlated with bridging capital, but is still less directly tied to bridging capital than the measure above. Similarly, effective size is less directly related to brokerage or coordination capital than the Godfather Index.

  32. For further discussion of how incentives for reciprocation and cooperation are dependent upon network structure, see Raub and Weesie (1990), Bloch et al. (2007, 2008), Karlan et al. (2009), Lippert and Spagnolo (2011), Ali and Miller (2016, 2013).

  33. For a few starting references on measuring reputation see List (2006), Berens and van Riel (2004), Wartick (2002).

  34. The fact that individuals in a community are more familiar with others in the community can also be productive, as it can help them predict how others will act and hence to coordinate their behaviors which can be productive (e.g., see Jackson and Xing 2018).

References

  • Akcigit U, Caicedo S, Miguelez E, Stantcheva S, Sterzi V (2016) Dancing with the stars: innovation through interactions. NBER working paper 24466

  • Aldrich DP (2012) Social, not physical, infrastructure: the critical role of civil society after the 1923 Tokyo earthquake. Disasters 36(3):398–419

    Google Scholar 

  • Ali N, Miller D (2013) Enforcing cooperation in networked societies. mimeo: UCSD

  • Ali N, Miller D (2016) Ostracism and favoritism. Am Econ Rev 106(8):2329–2348

    Google Scholar 

  • Anderson KA (2017) Skill networks and measures of complex human capital. Proc Natl Acad Sci 114(48):12720–12724

    Google Scholar 

  • Arrow KJ (2000) Observations on social capital. Soc Capi A Multifaceted Perspect (World Bank Publisher) 6(10):3–5

    Google Scholar 

  • Arrow KJ, Borzekowski R (2004) Limited network connections and the distribution of wages. FEDS Working Paper

  • Atkeson A, Kehoe PJ (1993) Industry evolution and transition: the role of information capital. Federal Reserve Bank Minneap Res Depart Staff Rep 162:1–31

    Google Scholar 

  • Bailey M, Cao R, Kuchler T, Stroebel J, Wong A (2018) Social Connectedness: measurement, determinants, and effect. J Econ Perspect 32(3):259–280

    Google Scholar 

  • Banerjee A, Chandrasekhar A, Duflo E, Jackson MO (2013) Diffusion of Microfinance. Science 341(6144):1236498

    Google Scholar 

  • Banerjee A, Chandrasekhar A, Duflo E, Jackson MO (2015) Using gossips to spread information: theory and evidence from two randomized controlled trials. Rev Econ Stud, forthcoming. working paper: http://ssrn.com/abstract=2425379. Accessed 19 Apr 2019

  • Banfield EC (1958) The moral basis of a backward society. Free Press, New York

    Google Scholar 

  • Berens G, van Riel C (2004) Corporate associations in the academic literature: three main streams of thought in the reputation measurement literature. Corp Reput Rev 7(2):161–178

    Google Scholar 

  • Blandy R (1967) Marshall on human capital: a note. J Polit Econ 75(6):874–875

    Google Scholar 

  • Bloch F, Genicot G, Ray D (2008) Informal insurance in social networks. J Econ Theory 143(1):36–58

    Google Scholar 

  • Bloch F, Genicot G, Ray D (2007) Reciprocity in groups and the limits to social capital. Am Econ Rev 97(2):65–69

    Google Scholar 

  • Bloch F, Jackson MO, Tebaldi P (2016) Centrality measures in networks. http://ssrn.com/abstract=2749124. Accessed 19 Apr 2019

  • Bonacich P (1987) Power and centrality: a family of measures. Am J Sociol 92:1170–1182

    Google Scholar 

  • Borgatti SP, Jones C, Everett MG (1998) Network measures of social capital. Connections 21(2):27–36

    Google Scholar 

  • Borgatti SP (2005) Centrality and network flow. Soc Netw 27:55–71

    Google Scholar 

  • Bourdieu P (1986) The forms of capital. In: Richardson JE (ed) Handbook of theory and research of for the sociology of education, pp 46–58

  • Brass DJ, Krackhardt D (1999) The social capital of twenty-first century leaders. In: Hun JG, Phillips RL (eds) Out-of-the-box leadership: Transforming the twenty-first-century army and other top-performing organizations, pp 179–194

  • Burt RS (1992) Structural holes: the social structure of competition. Harvard Univ. Press, Cambridge

    Google Scholar 

  • Burt RS (2000) The network structure of social capital. Res Organiz Behav 22:345–423

    Google Scholar 

  • Burt RS (2005) Brokerage and closure: an introduction to social capital. Oxford University Press, Oxford

    Google Scholar 

  • Coleman JS (1988) Social Capital in the creation of human capital. Am J Sociol 94(1):S95–S120

    Google Scholar 

  • Dasgupta P (2005) Economics of social capital. Econ. Record 81(s1):2–21

    Google Scholar 

  • Dasgupta P, Serageldin I (2001) Social capital: a multifaceted perspective. World Bank Publications, Washington, DC

    Google Scholar 

  • Durlauf SN (1999) The case “against” social capital. Social Systems Research Institute Focus, University of Wisconsin 20(3):1–6

    Google Scholar 

  • Ercsey-Ravasz M, Lichtenwalter RN, Chawla NV, Toroczkai Z (2012) Range-limited centrality measures in complex networks. Phys Rev E 85(6):066103

    Google Scholar 

  • Everett M, Borgatti SP (2005) Ego network betweenness. Soc Netw 27(1):31–38

    Google Scholar 

  • Everett MG, Valente TW (2016) Bridging, brokerage and betweenness. Soc Netw 44:202–208

    Google Scholar 

  • Flap H, Völker B (2001) Goal specific social capital and job satisfaction: effects of different types of networks on instrumental and social aspects of work. Soc Netw 23(4):297–320

    Google Scholar 

  • Freeman L (1977) A set of measures of centrality based on betweenness. Sociometry 40(1):35–41

    Google Scholar 

  • Glaeser EL, Laibson D, Sacerdote B (2002) An economic approach to social capital. Econ J 112(483):437–58

    Google Scholar 

  • Gould RV, Fernandez RM (1989) Structures of mediation: a formal approach to brokerage in transaction networks. Sociol Methodol 19:89–126

    Google Scholar 

  • Granovetter MS (1973) The strength of weak ties. Am J Sociol 78(6):1360–1380

    Google Scholar 

  • Hampton K, Wellman B (2003) Neighboring in netville: how the internet supports community and social capital in a wired suburb. City Commun 2(4):277–311

    Google Scholar 

  • Hanifan LJ (1916) The rural school community center. Ann Am Acad Polit Soc Sci 67(1):130–138

    Google Scholar 

  • Hanifan LJ (1920) The community center. Silver, Burdett

    Google Scholar 

  • Jackson MO (2008) Social and economic networks. Princeton University Press, Princeton

    Google Scholar 

  • Jackson MO (2019a) The friendship paradox and systematic biases in perceptions and social norms. J Polit Econ 127(2):777–818

    Google Scholar 

  • Jackson MO (2019b) The human network. Pantheon Books, New York

    Google Scholar 

  • Jackson MO, Malladi S, McAdams D (2018) Learning through the grapevine: the impact of message mutation, transmission failure, and deliberate bias. http://ssrn.com/abstract=3269543

  • Jackson MO, Rodriguez-Barraquer TR, Tan X (2012) Social capital and social quilts: network patterns of favor exchange. Am Econ Rev 102(5):1857–1897

    Google Scholar 

  • Jackson MO, Wolinsky A (1996) A strategic model of social and economic networks. J Econ Theory 71(1):44–74

    Google Scholar 

  • Jackson MO, Xing Y (2018) The complementarity between community and government in enforcing norms and contracts, and their interaction with religion and corruption. http://ssrn.com/abstract=3153842

  • Karlan D, Mobius M, Rosenblat T, Szeidl A (2009) Trust and social collateral. Q J Econ 24:1307–1361

    Google Scholar 

  • Katz L (1953) A new status index derived from sociometric analysis. Psychometrica 18:39–43

    Google Scholar 

  • Kawachi I, Kim D, Coutts A, Subramanian SV (2004) Commentary: reconciling the three accounts of social capital. Int J Epidemiol 33(4):682–690

    Google Scholar 

  • Kempe D, Kleinberg J, Tardos E (2003) Maximizing the spread of influence through a social network. Proc. 9th Intl. Conf. on Knowledge Discovery and Data Mining pp 137–146

  • Kempe D, Kleinberg J, Tardos E (2005) Influential nodes in a diffusion model for social networks. In Proc. 32nd Intl. Colloq. on Automata, Languages and Programming, pp 1127–1138

  • Kent D (1978) The rise of the medici: faction in florence 1426–1434. Oxford University Press, Oxford

    Google Scholar 

  • Kets W, Iyengar G, Sethi R, Bowles S (2011) Inequality and network structure. Games Econ Behav 73(1):215–226

    Google Scholar 

  • Klewes J, Wreschniok R (2009) Reputation capital. Springer, New York

    Google Scholar 

  • Knack S, Keefer P (1997) Does social capital have an economic payoff? A cross-country investigation. Q J Econ 112(4):1251–1288

    Google Scholar 

  • Laguna-Müggenburg E (2017) Using homophily to spread information: influencers need not be superstars. Stanford University, Mimeo

  • Lin N (1999) Building a network theory of social capital. Connections 22(1):28–51

    Google Scholar 

  • Lippert S, Spagnolo G (2011) Networks of relations and Word-of-Mouth communication. Games Econ Behav 72(1):20217

    Google Scholar 

  • List JA (2006) The behavioralist meets the market: measuring social preferences and reputation effects in actual transactions. J Polit Econ 114(1):1–37

    Google Scholar 

  • Loury G (1977) A dynamic theory of racial income differences. Women Minorities Employ Discrim 153:86–153

    Google Scholar 

  • Mailath GJ, Samuelson L (2006) Repeated games and reputations: long-run relationships. Oxford University Press, Oxford

    Google Scholar 

  • Manea M (2017) Bottleneck links, essential intermediaries, and competing paths of diffusion in networks. Mimeo

  • Nannicini T, Stella A, Tabellini G, Troiano U (2013) Social capital and political accountability. Am Econ J Econ Pol 5(2):222–250

    Google Scholar 

  • Padgett JF, Ansell CK (1993) Robust action and the rise of the Medici 1400–1434. Am J Sociol 98(6):1259–1319

    Google Scholar 

  • Pfeffer J (1981) Power in organizations. Pitman Publishing, Marshfield, MA

    Google Scholar 

  • Pfeffer J (1992) Managing with power: politics and influence in organizations. Harvard Business Press, Brighton

    Google Scholar 

  • Portes A (1998) Social capital: its origins and applications in modern sociology. Ann Rev Sociol 24(1):1–24

    Google Scholar 

  • Putnam RD (2000) Bowling alone: the collapse and revival of American Community. Simon and Schuster, New York

    Google Scholar 

  • Raub W, Weesie J (1990) Reputation and efficiency in social interactions: an example of network effects. Am J Sociol 96(3):62654

    Google Scholar 

  • Smith A (1776) An inquiry into the nature and causes of the wealth of nations. Strahan and Caldwell, London

  • Sobel J (2002) Can we trust social capital? J Econ Lit 40:139–154

    Google Scholar 

  • Solow RM (2000) Notes on social capital and economic performance. Soc Cap Multifac Persp (World Bank Publisher) 6(10):6–12

    Google Scholar 

  • Szreter S, Woolcock M (2004) Health by association? Social capital, social theory, and the political economy of public health. Int Jo Epidemiol 33(4):650–667

    Google Scholar 

  • Tabellini G (2010) Culture and institutions: economic development in the regions of Europe. J Eur Econ Assoc 8(4):677–716

    Google Scholar 

  • Wartick SL (2002) Measuring corporate reputation: Definition and data. Bus Soc 41(4):371–392

    Google Scholar 

  • Woolcock M (1998) Social capital and economic development: toward a theoretical synthesis and policy framework. Theory Soc 27(2):151–208

    Google Scholar 

Download references

Acknowledgements

I gratefully acknowledge financial support under ARO MURI Award No. W911NF-12-1-0509 and NSF Grant SES-1629446. I also thank Robert Fluegge, Eduardo Laguna-Muggenberg, Mihai Manea, Sharon Shiao, and two anonymous referees for helpful comments on earlier drafts.

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  1. Department of Economics, Stanford University, Stanford, CA, 94305-6072, USA

    Matthew O. Jackson

  2. Santa Fe Institute, Santa Fe, USA

    Matthew O. Jackson

  3. CIFAR, Toronto, Canada

    Matthew O. Jackson

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This was written for a special issue in memory of Kenneth J. Arrow. Conversations with Ken about social capital and the role of networks helped sharpen my thinking on the subject. It is sad not to have the opportunity to discuss this paper with him.

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Jackson, M.O. A typology of social capital and associated network measures. Soc Choice Welf 54, 311–336 (2020). https://doi.org/10.1007/s00355-019-01189-3

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