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Human-mobility networks, country income, and labor productivity

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  • FAGIOLO, GIORGIO
  • SANTONI, GIANLUCA

Abstract

This paper asks whether the level of integration of world countries in the international network of temporary human mobility can explain differences in their per-capita income and labor productivity. We disentangle the role played by global country centrality in the network from traditional openness measures, which only account for local, nearest-neighbor linkages through which ideas and knowledge can flow. Using 1995-2010 data, we show that global country centrality in the international temporary human-mobility network enhances both per-capita income and labor productivity. Our results hold cross-sectionally, as well as in a dynamic-panel estimation, and take into account potential endogeneity issues. Our findings imply that how close a country is to the theoretical technological frontier, depends not only on how much she is open to temporary human mobility, but mostly on whether she is embedded in a web of relationships connecting her with other influential partners in the network. Our exercises also suggest that most of the gain in income and productivity can be attained if country centrality in the network comes mostly from influential partners that lie not too far away from, but neither too close to them in the network.

Suggested Citation

  • Fagiolo, Giorgio & Santoni, Gianluca, 2015. "Human-mobility networks, country income, and labor productivity," Network Science, Cambridge University Press, vol. 3(3), pages 377-407, September.
  • Handle: RePEc:cup:netsci:v:3:y:2015:i:03:p:377-407_00
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    Cited by:

    1. Daryna Grechyna, 2020. "Current account and international networks," Review of International Economics, Wiley Blackwell, vol. 28(5), pages 1269-1294, November.
    2. Chakrabarti, Anindya S., 2018. "Dispersion in macroeconomic volatility between the core and periphery of the international trade network," Journal of Economic Dynamics and Control, Elsevier, vol. 88(C), pages 31-50.
    3. Matteo Barigozzi & Marc Hallin, 2017. "A network analysis of the volatility of high dimensional financial series," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(3), pages 581-605, April.
    4. Mihaela Peres & Helian Xu & Gang Wu, 2016. "Community Evolution in International Migration Top1 Networks," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-20, February.
    5. Jincheng Jiang & Jinsong Chen & Wei Tu & Chisheng Wang, 2019. "A Novel Effective Indicator of Weighted Inter-City Human Mobility Networks to Estimate Economic Development," Sustainability, MDPI, vol. 11(22), pages 1-18, November.
    6. Ayadi, Rym & Giovannetti, Giorgia & Marvasi, Enrico & Zaki, Chahir, 2024. "Trade networks and the productivity of MENA firms in global value chains," Structural Change and Economic Dynamics, Elsevier, vol. 69(C), pages 10-23.
    7. Matteo Barigozzi & Marc Hallin, 2015. "Networks, Dynamic Factors, and the Volatility Analysis of High-Dimensional Financial Series," Working Papers ECARES ECARES 2015-34, ULB -- Universite Libre de Bruxelles.

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