headerpos: 12198
 
 
 

Proceedings of the Estonian Academy of Sciences

ISSN 1736-7530 (electronic)   ISSN 1736-6046 (print)
Formerly: Proceedings of the Estonian Academy of Sciences, series Physics & Mathematics and  Chemistry
Published since 1952

Proceedings of the Estonian Academy of Sciences

ISSN 1736-7530 (electronic)   ISSN 1736-6046 (print)
Formerly: Proceedings of the Estonian Academy of Sciences, series Physics & Mathematics and  Chemistry
Published since 1952
Publisher
Journal Information
» Editorial Board
» Editorial Policy
» Archival Policy
» Article Publication Charges
» Copyright and Licensing Policy
Guidelines for Authors
» For Authors
» Instructions to Authors
» LaTex style files
Guidelines for Reviewers
» For Reviewers
» Review Form
Open Access
List of Issues
» 2019
Vol. 68, Issue 3
Vol. 68, Issue 2
Vol. 68, Issue 1
» 2018
» 2017
» 2016
» 2015
» 2014
» 2013
» 2012
» 2011
» 2010
» 2009
» 2008
» Back Issues Phys. Math.
» Back Issues Chemistry
» Back issues (full texts)
  in Google. Phys. Math.
» Back issues (full texts)
  in Google. Chemistry
» Back issues (full texts)
  in Google Engineering
» Back issues (full texts)
  in Google Ecology
» Back issues in ETERA Füüsika, Matemaatika jt
Subscription Information
» Prices
Internet Links
Support & Contact
Publisher
» Staff
» Other journals

Specific statistical properties of the strength of links and nodes of the Estonian network of payments; pp. 235–243

(Full article in PDF format) https://doi.org/10.3176/proc.2019.3.02


Authors

Stephanie Rendón de la Torre, Jaan Kalda, Robert Kitt

Abstract

We investigated the strength of the interactions of the elements of the Estonian network of payments (link weight of payments and volume of payments) by the realization of particular experiments. Specific statistical measures of this network, which combine the topology of the relations of the strength of links and nodes and their specific weights, were studied with the purpose of discovering beyond the topological architecture of our network and revealing aspects of its complex structure. Moreover, scale-free properties between the strengths and the degree values were found. We also identified clear patterns of structural changes in such a network over the analysed period.

Keywords

economic networks, complex systems, scale-free networks, weighted networks, strength of nodes.

References

    1.  Newman , M. E. J. Networks: An introduction. Oxford University Press , 2010.
https://doi.org/10.1093/acprof:oso/9780199206650.001.0001

    2.  Strogatz , S. H. Exploring complex networks. Nature , 2001 , 410 , 268–276.
https://doi.org/10.1038/35065725

    3.  Albert , R. and Barabási , A. L. Statistical mechanics of complex networks. Rev. Mod. Phys. , 2002 , 74 , 47–91.
https://doi.org/10.1103/RevModPhys.74.47

    4.  Liu , Y. Y. and Barabási , A. L. Control principles of complex systems. Rev. Mod. Phys. , 2016 , 88(3) , 035006–035064.
https://doi.org/10.1103/RevModPhys.88.035006

    5.  Faloutsos , M. , Faloutsos , P. , and Faloutsos , C. On power-law relationships of the internet topology. ACM SIGCOMM Comput. Commun. Rev. , 1999 , 9(4) , 251–262.
https://doi.org/10.1145/316194.316229

    6.  Albert , R. , Jeong , H. , and Barabási , A. L. Diameter of the world wide web. Nature , 1999 , 401 , 130–131.
https://doi.org/10.1038/43601

    7.  Pagani , G. A. and Aiello , M. The power grid as a complex network: a survey. Physica A , 2013 , 392(11) , 2688–2700.
https://doi.org/10.1016/j.physa.2013.01.023

    8.  Newman , M. E. J. Scientific collaboration networks. I. Network construction and fundamental results. Phys. Rev. E , 2001 , 64(1) , 016131.
https://doi.org/10.1103/PhysRevE.64.016131

    9.  Davidsen , J. , Ebel , H. , and Bornholdt , S. Emergence of a small world from local interactions: modeling acquaintance networks. Phys. Rev. Lett. , 2002 , 88(12) , 128701.
https://doi.org/10.1103/PhysRevLett.88.128701

 10.  Jeong , H. , Tombor , B. , Albert , R. , Oltvai , Z. N. , and Barabási , A. L. The large-scale organization of metabolic networks. Nature , 2000 , 407(6804) , 651–654.
https://doi.org/10.1038/35036627

 11.  Doye , J. Network topology of a potential energy landscape: a static scale-free network. Phys. Rev. Lett. , 2002 , 88(23) , 238701.
https://doi.org/10.1103/PhysRevLett.88.238701

 12.  Guimerà , R. and Amaral , L. A. N. Modeling the world-wide airport network. Eur. J. Phys. B , 2004 , 38(2) , 381–385.
https://doi.org/10.1140/epjb/e2004-00131-0

 13.  Inaoka , H. , Nimoniya , T. , Taniguchi , K. , Shimizu , T. , and Takayasu , H. Fractal network derived from banking transactions – an analysis of network structures formed by financial institutions. Bank of Japan Working Papers , 2004.

 14.  Watts , D. J. Small Worlds: The Dynamics of Networks Between Order and Randomness. Princeton University Press , NJ , 2003.

 15.  Barabási , A. L. Scale-free networks: a decade and beyond science. Science , 2009 , 325(5939) , 412–413.
https://doi.org/10.1126/science.1173299

 16.  Rendón de la Torre , S. , Kalda , J. , Kitt , R. , and Engelbrecht , J. On the topologic structure of economic complex networks: empirical evidence from large scale payment network of Estonia. Chaos Solitons Fractals , 2016 , 90 , 18–27.
https://doi.org/10.1016/j.chaos.2016.01.018

 17.  Barrat , A. , Barthelemy , M. , Pastor-Satorras , R. , and Vespignani , A. The architecture of complex weighted networks. Proc. Natl Acad. Sci. USA , 2004 , 101(11) , 3747–3752.
https://doi.org/10.1073/pnas.0400087101

 18.  Opsahl , T. , Agneessens , F. , and Skvoretz , J. Node centrality in weighted networks: generalizing degree and shortest paths. Soc. Networks , 2010 , 32(3) , 245–251.
https://doi.org/10.1016/j.socnet.2010.03.006

 19.  Xiang , J. , Hu , K. , Zhang , Y. , Hu , T. , and Li , J. M. Analysis and perturbation of degree correlation in complex networks. Europhys. Lett. , 2015 , 111(4) , 48003.
https://doi.org/10.1209/0295-5075/111/48003

 20.  Boguña , M. and Pastor-Satorras , R. Epidemic spreading in correlated complex networks. Phys. Rev. E , 2002 , 66(4) , 047104.
https://doi.org/10.1103/PhysRevE.66.047104

 21.  Nie , T. , Guo , Z. , Zhao , K. , and Zhe-Ming , Lu. The dynamic correlation between degree and betweenness of complex network under attack. Physica A , 2016 , 457(1) , 129–137.
https://doi.org/10.1016/j.physa.2016.03.075

 22.  Zemp , D. C. , Wiedermann , M. , Kurths , J. , Rammig , A. , and Donges , J. F. Node-weighted measures for complex networks with directed and weighted edges for studying continental moisture recycling. Europhys. Lett. , 2014 , 107(5) , 58005.
https://doi.org/10.1209/0295-5075/107/58005

 23.  Newman , M. E. J. Analysis of weighted networks. Phys. Rev. E , 2004 , 70(5) , 056131.
https://doi.org/10.1103/PhysRevE.70.056131

 24.  Souma , W. , Fujiwara , Y. , and Aoyama , H. Heterogeneous economic networks. In The Complex Networks of Economic Interactions (Namatame , A. , Kaizouji , T. , and Aruka , Y. , eds) , Lecture Notes in Economics and Mathematical Systems , 2006 , 567 , 79–92. Springer , Berlin , Heidelberg.
https://doi.org/10.1007/3-540-28727-2_5

 25.  Rotundo , G. and D’Arcangelis , A. M. Ownership and control in shareholding networks. J. Econ. Interact Coord. , 2010 , 5(2) , 191–219.
https://doi.org/10.1007/s11403-010-0068-4

 26.  Reyes , J. , Schiavo , S. , and Fagiolo , G. Assessing the evolution of international economic integration using random-walk betweenness centrality: the cases of East Asia and Latin America. Advs. Complex Syst. , 2007 , 11(5) , 685–702.
https://doi.org/10.1142/S0219525908001945

 27.  Battiston , S. , Rodrigues , J. F. , and Zeytinoglu , H. The network of inter-regional direct investment stocks across Europe. Advs. Complex Syst. , 2007 , 10(1) , 29–51.
https://doi.org/10.1142/S0219525907000933

 28.  Glattfelder , J. B. and Battiston , S. Backbone of complex networks of corporations: the flow of control. Phys. Rev. E , 2009 , 80(3) , 036104.
https://doi.org/10.1103/PhysRevE.80.036104

 29.  Nakano , T. and White , D. Network structures in industrial pricing: the effect of emergent roles in Tokyo supplier-chain hierarchies. Struct. and Dyn. , 2007 , 2(3) , 130–154.

 30.  Lublóy , A. Topology of the Hungarian large-value transfer system. Magyar Nemzeti Bank (Central Bank of Hungary) MNB Occasional Papers , 2006 , 57.

 31.  Soramäki , K. , Bech , M. L. , Arnold , J. , Glass , R. J. , and Beyeler , W. E. The topology of interbank payment flows. Physica A , 2007 , 379(1) , 317–333.
https://doi.org/10.1016/j.physa.2006.11.093

 32.  Boss , M. , Helsinger , H. , Summer , M. , and Thurner , S. The network topology of the interbank market. Quant. Finance , 2004 , 4(6) , 677–684.
https://doi.org/10.1080/14697680400020325

 33.  Iori , G. and Jafarey , S. Criticality in a model of banking crisis. Physica A , 2001 , 299(1) , 205–212.
https://doi.org/10.1016/S0378-4371(01)00297-7

 34.  Iori , G. , De Masi , G. , Precup , O. V. , Gabbi , G. , and Caldarelli , G. A network analysis of the Italian overnight money market. J. Econ. Dyn. Control. , 2007 , 32(1) , 259–278.
https://doi.org/10.1016/j.jedc.2007.01.032

 35.  Safdari , H. , Zare Kamali , M. , Shirazi , A. , Khalighi , M. , Jafari , G. , and Ausloos , M. Fractional dynamics of network growth constrained by aging node interactions. PLOS ONE , 2016 , 11(5) , e0154983.
https://doi.org/10.1371/journal.pone.0154983

 36.  Varela , L. M. , Rotundo , G. , Ausloos , M. , and Carrete Montana , J. Complex network analysis in socioeconomic models. In Complexity and Geographical Economics (Commendatore , P. , Kayam , S. , and Kubin , I. , eds) , Dynamic Modeling and Econometrics in Economics and Finance , 2015 , 19. Springer , Cham.
https://doi.org/10.1007/978-3-319-12805-4_9

 37.  Chapelle , A. and Szafarz , A. Controlling firms through the majority voting rule. Physica A , 2005 , 355(2–4) , 509–529.
https://doi.org/10.1016/j.physa.2005.03.026

 38.  Kaluza , P. , Kölzsch , A. , Gastner , M. T. , and Blasius , B. The complex network of global cargo ship movements. J. R. Soc. Interface , 2010 , 7(48) , 1093–1103.
https://doi.org/10.1098/rsif.2009.0495

 
Back

Current Issue: Vol. 68, Issue 3, 2019




Publishing schedule:
No. 1: 20 March
No. 2: 20 June
No. 3: 20 September
No. 4: 20 December