Bipartite networks provide new insights on international trade markets

Maximiliano Fernandez; Javier Galeano; Cesar Hidalgo

doi:10.3934/nhm.2012.7.399

Article Contents

2012, Volume 7, Issue 3: 399-413. Doi: 10.3934/nhm.2012.7.399

This issue Previous Article Modeling international crisis synchronization in the world trade web Next Article Structural properties of urban bus and subway networks of Madrid

Bipartite networks provide new insights on international trade markets

1.
Grupo de Sistemas Complejos, Universidad Politécnica de Madrid
2.
Grupo de Sistemas Complejos, E.U.I.T Agrícola, Universidad Politécnica de Madrid
3.
The Media Laboratory, Massachusetts Institute of Technology, Cambridge, MA

Received: December 2011

Revised: June 2012

Published: September 2012

Abstract / Introduction Related Papers Cited by

Abstract

Adam Smith is considered the father of modern economics. His research on the Wealth of Nations [10] is the first scientific work that theorized about the complexity of economic systems and how an invisible hand self-regulates markets and their behavior. In this way, we study international trade markets as complex networks. We analyze their topological properties, structure and temporal dynamics based on actual data. Our main premise states that trade networks are bipartite in nature because importers and exporters play a different role in the system. We apply a methodology developed for mutualistic ecosystems, finding minor gaps in it. We address such gaps by using well-known techniques from other related scientific work. The evidence supports the fact that our premise is a realistic hypothesis.

Keywords:

Mathematics Subject Classification: Primary: 58F15, 58F17; Secondary: 53C35.

Citation:

Related Papers

Cited by

References

[1]	B. Balassa, Comparative advantage in manufactured goods: A reappraisal, Rev. Econ. Stat., 68 (1986), 315-319.doi: 10.2307/1925512.
[2]	A. Barrat, M. Barthelemy, R. Pastor-Satorras and A. Vespignani, The architecture of complex weighted networks, Proc. Nat. Acad. Sci., 101 (2004), 3747-3752.doi: 10.1073/pnas.0400087101.
[3]	M. Bastian, S. Heymann and M. Jacomy, "Gephi: An Open Source Software for Exploring and Manipulating Networks," International AAAI Conference on Weblogs and Social Media, 2009.
[4]	G. Fagiolo, J. Reyes and S. Schiavo, World-trade web: Topological properties, dynamics and evolution, Phys. Rev. E, 79 (2009), 036115.doi: 10.1103/PhysRevE.79.036115.
[5]	L. J. Gilarranz, J. M. Pastor and J. Galeano, The architecture of weighted mutualistic networks, Oikos, 121 (2012), 1154-1162.doi: 10.1111/j.1600-0706.2011.19592.x.
[6]	C. A. Hidalgo, B. Klinger, A. L. Barabási and R. Hausmann, The product space conditions the development of nations, Science, 317 (2007), 482-487.doi: 10.1126/science.1144581.
[7]	P. G. Lind, M. C. González and H. J. Herrmann, Cycles and clustering in bipartite networks, Physical Review E, 72 (2005), 056127.
[8]	M. A. Serrano and M. Borguna, Topology of the world trade web, Phys. Rev. E, 68 (2003), 015101(R).doi: 10.1103/PhysRevE.68.015101.
[9]	M. A. Serrano, M. Borguna and A. Vespignani, Patterns of dominant flows in the world trade web, J. Econ. Interac. Coord., 2 (2007), 111-124.
[10]	A. Smith, "An Inquiry Into The Nature And Cause Of The Wealth of Nations," W. Strahan and T. Cadell, London, 1776.
[11]	T. Squartini, G. Fagiolo and D. Garlaschelli, Randomizing world trade. I. A binary network analysis, Phys. Rev. E, 84 (2011), 046117.doi: 10.1103/PhysRevE.84.046118.
[12]	T. Squartini, G. Fagiolo and D. Garlaschelli, Randomizing world trade. II. A weighted network analysis, Phys. Rev. E, 84 (2011), 046118.doi: 10.1103/PhysRevE.84.046118.
[13]	"United Nations Commodity Trade Statistics Database (UN Comtrade)," 2011. Available from: http://comtrade.un.org/db/.