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Social Networks and the Process of Globalization

Author

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  • Georg Duernecker
  • Fernando Vega-Redondo

Abstract

We propose a stylized dynamic model to understand the role of social networks in the phenomenon we call “globalization”. In a nutshell, this term refers to the process by which even agents who are geographically far apart come to interact, thus being able to overcome what would otherwise be a fast saturation of local opportunities. A key feature of our model is that the social network is the main channel through which agents exploit new opportunities. Therefore, only if the social network becomes global (heuristically, it “reaches far in few steps”) can global interaction be steadily sustained. An important insight derived from the model is that, for the social network to turn global, the long-range links required (bridges) cannot endogenously arise unless the matching mechanism displays significant local structure (cohesion). This sheds novel light on the dichotomy between bridging and cohesion that has long played a prominent role in the socio-economic literature. Our analysis also relates the process of globalization to other features of the environment such as the quality of institutions or the arrival rate of fresh ideas. The model is partially studied analytically for a limit scenario with a continuum population and is fully solved numerically for finite-population contexts.

Suggested Citation

  • Georg Duernecker & Fernando Vega-Redondo, 2018. "Social Networks and the Process of Globalization," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(3), pages 1716-1751.
    • Handle: RePEc:oup:restud:v:85:y:2018:i:3:p:1716-1751.
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    File URL: http://hdl.handle.net/10.1093/restud/rdx054
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    Cited by:

    1. Dürnecker, Georg & Meyer, Moritz & Vega-Redondo, Fernando, 2014. "The Network Origins of Economic Growth," Working Papers 14-06, University of Mannheim, Department of Economics.
    2. Georg Duernecker & Moritz Meyer & Fernando Vega‐Redondo, 2022. "Trade openness and growth: A network‐based approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1182-1203, September.
    3. Has van Vlokhoven, 2023. "Diffusion of Ideas in Networks with Endogenous Search," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 49, pages 269-311, July.
    4. Bramoullé, Yann & Kranton, Rachel E., 2024. "Altruism networks and economic relations," Journal of Economic Behavior & Organization, Elsevier, vol. 226(C).
    5. Francesco Lamperti & Franco Malerba & Roberto Mavilia & Giorgio Tripodi, 2019. "Does the Position in the Inter-sectoral Knowledge Space affect the International Competitiveness of Industries?," LEM Papers Series 2019/23, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

    More about this item

    Keywords

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    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • O17 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Formal and Informal Sectors; Shadow Economy; Institutional Arrangements
    • O43 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Institutions and Growth

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