Differential Network Effects on Economic Outcomes: A Structural Perspective

  • Eaman Jahani
  • Guillaume Saint-Jacques
  • Pål Sundsøy
  • Johannes Bjelland
  • Esteban Moro
  • Alex ‘Sandy’ Pentland
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10540)

Abstract

In a study of about 33,000 individuals in a south Asian country, we find that structural diversity, measured as the fraction of open triads in an ego-network, shows a relatively strong association with individual income. After including all the relevant control variables, the effect of structural diversity becomes exclusive to the highly educated individuals. We hypothesize these results are due to concentrated distribution of economic opportunities among the highly educated social strata combined with homophily among members of the same group. This process leads to two important societal consequences: extra network advantages for the highly educated, similar to the rich club effect, and inadequate diffusion of economic opportunities to the low educated social strata.

Keywords

Ego-networks Structural diversity Income Social status 

References

  1. 1.
    Åberg, Y., Hedström, P.: Youth unemployment : a self-reinforcing process?. In: Demeulenaere, P. (ed.) Analytical Sociology and Social Mechanisms, p. 201. Cambridge University Press, New York (2011)Google Scholar
  2. 2.
    Blau, P.M., Duncan, O.D.: The American Occupational Structure, vol. 33 (1968)Google Scholar
  3. 3.
    Burt, R.S.: Structural holes and good ideas. Am. J. Sociol. 110(2), 349–399 (2004)CrossRefGoogle Scholar
  4. 4.
    Christakis, N., Fowler, J.: The collective dynamics of smoking in a large social network. N. Engl. J. Med. 21358(22), 2249–2258 (2007)Google Scholar
  5. 5.
    Eagle, N., Macy, M., Claxton, R.: Network diversity and economic development. Science 335, 1215–1220 (2012)CrossRefMATHGoogle Scholar
  6. 6.
    Elliott, J.R.: Social isolation and labor market insulation: network and neighborhood effects on less-educated urban workers. Sociol. Q. 40(2), 199–216 (1999)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Epple, D., Romano, R.E.: Peer effects in education: a survey of the theory and evidence. Handb. Soc. Econ. 1(1B), 1053–1163 (2011)CrossRefGoogle Scholar
  8. 8.
    Granovetter, M.: The strength of weak ties. J. Sociol. 78(6), 1360–1380 (1973)Google Scholar
  9. 9.
    Granovetter, M.: Economic action and social structure: the problem of embeddedness. Am. J. Sociol. 91(3), 481–510 (1985)CrossRefGoogle Scholar
  10. 10.
    Granovetter, M.S.: Getting a Job: A Study of Contacts and Careers, vol. 25. University of Chicago Press, Chicago (1996)Google Scholar
  11. 11.
    Ioannides, Y.M., Datcher, L.: Job information networks, neighborhood effects, and inequality. J. Econ. Lit. 42(4), 1056–1093 (2004)CrossRefGoogle Scholar
  12. 12.
    Kish, L.: A procedure for objective respondent selection within the household. J. Am. Stat. Assoc. 44(247), 380 (1949)CrossRefGoogle Scholar
  13. 13.
    Lin, N., Ensel, W.M., Vaughn, J.C.: Social resources and strength of ties : structural factors in occupational status attainment. Am. Sociol. Rev. 46(4), 393–405 (1981)CrossRefGoogle Scholar
  14. 14.
    Lin, N., Ensel, W.M., Vaughn, J.C.: Social resources and occupational status attainment. Am. Sociol. Rev. 59(46), 393–405 (1981)CrossRefGoogle Scholar
  15. 15.
    Luo, S., Morone, F., Sarraute, C., Travizano, M., Makse, H.A.: Inferring personal economic status from social network location. Nat. Commun. 8 (2017). 15227Google Scholar
  16. 16.
    Marmaros, D., Sacerdote, B.: Peer and social networks in job search. Eur. Econ. Rev. 46(4–5), 870–879 (2002)CrossRefGoogle Scholar
  17. 17.
    McDonald, S., Lin, N., Ao, D.: Networks of opportunity: gender, race, and job leads. Soc. Probl. 56(3), 385–402 (2009)CrossRefGoogle Scholar
  18. 18.
    Reagans, R., Mcevily, B.: Source network structure and knowledge transfer: the effects of cohesion and range. Adm. Sci. Q. 48(2), 240–267 (2012)CrossRefGoogle Scholar
  19. 19.
    Reagans, R., Zuckerman, E.W.: Networks, diversity, and productivity: the social capital of corporate R&D teams. Organ. Sci. 12(4), 502–517 (2001)CrossRefGoogle Scholar
  20. 20.
    Wu, L., Waber, B., Brynjolfsson, E., Pentland, A.S.: Mining face-to-face interaction networks using socimetric badges: predicting productivity in an ITC configuation task. In: ICIS. pp. 1–19 (2008)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Eaman Jahani
    • 1
  • Guillaume Saint-Jacques
    • 2
  • Pål Sundsøy
    • 3
  • Johannes Bjelland
    • 3
  • Esteban Moro
    • 4
    • 5
  • Alex ‘Sandy’ Pentland
    • 1
    • 5
  1. 1.Institute for Data, Systems and SocietyMITCambridgeUSA
  2. 2.Sloan School of ManagementMITCambridgeUSA
  3. 3.Telenor Group ResearchFornebuNorway
  4. 4.Universidad Carlos III de MadridMadridSpain
  5. 5.Media LabMITCambridgeUSA

Personalised recommendations