American Institute of Mathematical Sciences

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September  2012, 7(3): 399-413. doi: 10.3934/nhm.2012.7.399

Bipartite networks provide new insights on international trade markets

Maximiliano Fernandez 1, , Javier Galeano 2, and  Cesar Hidalgo 3,

1. 

Grupo de Sistemas Complejos, Universidad Politécnica de Madrid, Spain
2. 

Grupo de Sistemas Complejos, E.U.I.T Agrícola, Universidad Politécnica de Madrid, Spain
3. 

The Media Laboratory, Massachusetts Institute of Technology, Cambridge, MA, United States

Received  December 2011 Revised  June 2012 Published  October 2012

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: markets, economics, Bipartite netwoks., Complex networks, mutualism.
Mathematics Subject Classification: Primary: 58F15, 58F17; Secondary: 53C3.
Citation: Maximiliano Fernandez, Javier Galeano, Cesar Hidalgo. Bipartite networks provide new insights on international trade markets. Networks & Heterogeneous Media, 2012, 7 (3) : 399-413. doi: 10.3934/nhm.2012.7.399
References:
[1]

B. Balassa, Comparative advantage in manufactured goods: A reappraisal, Rev. Econ. Stat., 68 (1986), 315-319. doi: 10.2307/1925512.  Google Scholar

[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.  Google Scholar

[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. Google Scholar

[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.  Google Scholar

[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.  Google Scholar

[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.  Google Scholar

[7]

P. G. Lind, M. C. González and H. J. Herrmann, Cycles and clustering in bipartite networks, Physical Review E, 72 (2005), 056127. Google Scholar

[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.  Google Scholar

[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. Google Scholar

[10]

A. Smith, "An Inquiry Into The Nature And Cause Of The Wealth of Nations," W. Strahan and T. Cadell, London, 1776. Google Scholar

[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.  Google Scholar

[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.  Google Scholar

[13]

, "United Nations Commodity Trade Statistics Database (UN Comtrade),", 2011. Available from: , ().   Google Scholar

show all references

References:
[1]

B. Balassa, Comparative advantage in manufactured goods: A reappraisal, Rev. Econ. Stat., 68 (1986), 315-319. doi: 10.2307/1925512.  Google Scholar

[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.  Google Scholar

[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. Google Scholar

[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.  Google Scholar

[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.  Google Scholar

[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.  Google Scholar

[7]

P. G. Lind, M. C. González and H. J. Herrmann, Cycles and clustering in bipartite networks, Physical Review E, 72 (2005), 056127. Google Scholar

[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.  Google Scholar

[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. Google Scholar

[10]

A. Smith, "An Inquiry Into The Nature And Cause Of The Wealth of Nations," W. Strahan and T. Cadell, London, 1776. Google Scholar

[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.  Google Scholar

[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.  Google Scholar

[13]

, "United Nations Commodity Trade Statistics Database (UN Comtrade),", 2011. Available from: , ().   Google Scholar

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