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Null models of economic networks: the case of the world trade web

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  • Giorgio Fagiolo

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  • Tiziano Squartini

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  • Diego Garlaschelli

    ()

Abstract

In all empirical-network studies, the observed properties of economic networks are informative only if compared with a well-defined null model that can quantitatively predict the behavior of such properties in constrained graphs. However, predictions of the available null-model methods can be derived analytically only under assumptions (e.g., sparseness of the network) that are unrealistic for most economic networks like the world trade web (WTW). In this paper we study the evolution of the WTW using a recently-proposed family of null network models. The method allows to analytically obtain the expected value of any network statistic across the ensemble of networks that preserve on average some local properties, and are otherwise fully random. We compare expected and observed properties of the WTW in the period 1950–2000, when either the expected number of trade partners or total country trade is kept fixed and equal to observed quantities. We show that, in the binary WTW, node-degree sequences are sufficient to explain higher-order network properties such as disassortativity and clustering-degree correlation, especially in the last part of the sample. Conversely, in the weighted WTW, the observed sequence of total country imports and exports are not sufficient to predict higher-order patterns of the WTW. We discuss some important implications of these findings for international-trade models. Copyright Springer-Verlag 2013

Suggested Citation

  • Giorgio Fagiolo & Tiziano Squartini & Diego Garlaschelli, 2013. "Null models of economic networks: the case of the world trade web," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(1), pages 75-107, April.
  • Handle: RePEc:spr:jeicoo:v:8:y:2013:i:1:p:75-107 DOI: 10.1007/s11403-012-0104-7
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Fariba Karimi & Matthias Raddant, 2016. "Cascades in Real Interbank Markets," Computational Economics, Springer;Society for Computational Economics, vol. 47(1), pages 49-66, January.
    2. Assaf Almog & Rhys Bird & Diego Garlaschelli, 2015. "Enhanced Gravity Model of trade: reconciling macroeconomic and network models," Papers 1506.00348, arXiv.org, revised Mar 2017.
    3. Marco Dueñas & Giorgio Fagiolo, 2013. "Modeling the International-Trade Network: a gravity approach," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(1), pages 155-178, April.
    4. Marco Dueñas & Giorgio Fagiolo, 2014. "Global Trade Imbalances: A Network Approach," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 17(03n04), pages 1-29.
    5. Leonardo Bargigli & Giovanni di Iasio & Luigi Infante & Fabrizio Lillo & Federico Pierobon, 2015. "Interbank markets and multiplex networks: centrality measures and statistical null models," Papers 1501.05751, arXiv.org.
    6. Marcos Duenas & Rossana Mastrandrea & Matteo Barigozzi & Giorgio Fagiolo, 2017. "Spatio-Temporal Patterns of the International Merger and Acquisition Network," LEM Papers Series 2017/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    7. Leonidov, A.V. & Rumyantsev, E.L., 2016. "Default contagion risks in Russian interbank market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 36-48.
    8. Halkos, George & Tsilika, Kyriaki, 2016. "Assessing classical input output structures with trade networks: A graph theory approach," MPRA Paper 72511, University Library of Munich, Germany.
    9. Kırer, Hale & Çırpıcı, Yasemin & Eren, Ercan, 2013. "Complex Networks Analysis of European International Trade: An Agent-Based Model," EY International Congress on Economics I (EYC2013), October 24-25, 2013, Ankara, Turkey 243, Ekonomik Yaklasim Association.

    More about this item

    Keywords

    World trade web; Null models of networks; Complex networks; International trade; D85; C49; C63; F10;

    JEL classification:

    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • F10 - International Economics - - Trade - - - General

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