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Germs, Social Networks and Growth

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  • Alessandra Fogli
  • Laura Veldkamp

Abstract

Does the pattern of social connections between individuals matter for macroeconomic outcomes? If so, where do these differences come from and how large are their effects? Using network analysis tools, we explore how different social network structures affect technology diffusion and thereby a country's rate of growth. The model also explains how different social networks may emerge endogenously in response to the prevalence of infectious disease. Initial differences in disease prevalence can produce different network structures, leading to divergent levels of income. We compare calibrated model predictions with data. The model and data agree that a one-standard-deviation increase in our index of network diffusion speed results in output growth that is 1/2% higher per year.

Suggested Citation

  • Alessandra Fogli & Laura Veldkamp, 2012. "Germs, Social Networks and Growth," NBER Working Papers 18470, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:18470
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    Cited by:

    1. Javier Mejia, 2018. "Social Interactions and Modern Economic Growth," Working Papers 20180021, New York University Abu Dhabi, Department of Social Science, revised Sep 2018.
    2. Viktor Stojkoski & Zoran Utkovski & Petar Jolakoski & Dragan Tevdovski & Ljupco Kocarev, 2020. "The socio-economic determinants of the coronavirus disease (COVID-19) pandemic," Papers 2004.07947, arXiv.org, revised Nov 2020.
    3. Lindner, Ines & Strulik, Holger, 2014. "From tradition to modernity: Economic growth in a small world," Journal of Development Economics, Elsevier, vol. 109(C), pages 17-29.
    4. Maria Rosaria Carillo & Vincenzo Lombardo & Alberto Zazzaro, 2019. "The rise and fall of family firms in the process of development," Journal of Economic Growth, Springer, vol. 24(1), pages 43-78, March.
    5. Tiago V. V. Cavalcanti & Chryssi Giannitsarou, 2017. "Growth and Human Capital: A Network Approach," Economic Journal, Royal Economic Society, vol. 127(603), pages 1279-1317, August.
    6. Elsner, Benjamin & Narciso, Gaia & Thijssen, Jacco J. J., 2013. "Migrant Networks and the Spread of Misinformation," IZA Discussion Papers 7863, Institute of Labor Economics (IZA).
    7. Saad, Mohsen & Samet, Anis, 2020. "Collectivism and commonality in liquidity," Journal of Business Research, Elsevier, vol. 116(C), pages 137-162.
    8. Paolo Zeppini & Koen Frenken & Luis R. Izquierdo, 2013. "Innovation diffusion in networks: the microeconomics of percolation," Working Papers 13-02, Eindhoven Center for Innovation Studies, revised Feb 2013.
    9. Dutz, Mark A., 2013. "Resource reallocation and innovation : converting enterprise risks into opportunities," Policy Research Working Paper Series 6534, The World Bank.
    10. Zhu, J., 2018. "The agricultural root of innovation in China," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277219, International Association of Agricultural Economists.

    More about this item

    JEL classification:

    • E02 - Macroeconomics and Monetary Economics - - General - - - Institutions and the Macroeconomy
    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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