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Social Networks and the Process of "Globalization"

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  • Georg Duernecker
  • Fernando Vega-Redondo

Abstract

We propose a stylised dynamic model to understand the role of social networks in the phenomenon we call "globalization." 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. To shed light on the conditionsunder which such a transformation may, or may not, take place is the main objective of the paper. One of the main insights arising from the model is that, in order for the social network to turn global, the economy needs to display a degree of \geographical cohesion" that is neither too high (for then global opportunities simply do not arise) nor too low (then the meeting mechanism displays too little structure for the process to take off). But if globalization does materialize, we show that it is a robust state of affairs that often arises abruptly as key parameters change. This occurs, in particular, as the rate of arrival of ideas rises, or when there is a high enough increase in the range at which the network transmits information.

Suggested Citation

  • Georg Duernecker & Fernando Vega-Redondo, 2012. "Social Networks and the Process of "Globalization"," Economics Working Papers ECO2012/25, European University Institute.
  • Handle: RePEc:eui:euiwps:eco2012/25
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. 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.
    3. Dürnecker, Georg & Meyer, Moritz & Vega-Redondo, Fernando, 2014. "The Network Origins of Economic Growth," Working Papers 14-06, University of Mannheim, Department of Economics.
    4. 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.

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    More about this item

    Keywords

    D83; D85; C73; O17; O43;
    All these keywords.

    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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