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Modeling the International-Trade Network: A Gravity Approach

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  • Marco Duenas
  • Giorgio Fagiolo

Abstract

This paper investigates whether the gravity model (GM) can explain the statistical properties of the International Trade Network (ITN). We fit data on international-trade flows with a GM specification using alternative fitting techniques and we employ GM estimates to build a weighted predicted ITN, whose topological properties are compared to observed ones. Furthermore, we propose an estimation strategy to predict the binary ITN with a GM. We find that the GM successfully replicates the weighted-network structure of the ITN, only if one fixes its binary architecture equal to the observed one. Conversely, the GM performs very badly when asked to predict the presence of a link, or the level of the trade flow it carries, whenever the binary structure must be simultaneously estimated.

Suggested Citation

  • Marco Duenas & Giorgio Fagiolo, 2011. "Modeling the International-Trade Network: A Gravity Approach," LEM Papers Series 2011/25, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  • Handle: RePEc:ssa:lemwps:2011/25
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    References listed on IDEAS

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    Cited by:

    1. Douma, J.C. & Pautasso, M. & Venette, R.C. & Robinet, C. & Hemerik, L. & Mourits, M.C.M. & Schans, J. & van der Werf, W., 2016. "Pathway models for analysing and managing the introduction of alien plant pests an overview and categorization," Ecological Modelling, Elsevier, vol. 339(C), pages 58-67.
    2. Chiarucci, Riccardo & Ruzzenenti, Franco & Loffredo, Maria I., 2014. "Detecting spatial homogeneity in the World Trade Web with Detrended Fluctuation Analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 401(C), pages 1-7.
    3. repec:eee:energy:v:141:y:2017:i:c:p:1226-1238 is not listed on IDEAS
    4. 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.
    5. 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.
    6. Angela Abbate & Luca De Benedictis & Giorgio Fagiolo & Lucia Tajoli, 2012. "The International Trade Network in Space and Time," LEM Papers Series 2012/17, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    7. 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.
    8. Brooks, Douglas H. & Ferrarini, Benno, 2014. "Vertical gravity," Journal of Asian Economics, Elsevier, vol. 31, pages 1-9.
    9. Riccardo Chiarucci & Franco Ruzzenenti & Maria I. Loffredo, 2013. "Detecting spatial homogeneity in the world trade web with Detrended Fluctuation Analysis," Papers 1308.0526, arXiv.org, revised Nov 2013.
    10. Kym Anderson & Joseph Francois & Douglas Nelson & Glyn Wittwer, 2016. "Intra-industry Trade in a Rapidly Globalizing Industry: The Case of Wine," Review of International Economics, Wiley Blackwell, vol. 24(4), pages 820-836, September.
    11. Francesco Picciolo & Tiziano Squartini & Franco Ruzzenenti & Riccardo Basosi & Diego Garlaschelli, 2012. "The role of distances in the World Trade Web," Papers 1210.3269, arXiv.org, revised Oct 2012.
    12. Mika J. Straka & Guido Caldarelli & Tiziano Squartini & Fabio Saracco, 2017. "From Ecology to Finance (and Back?): Recent Advancements in the Analysis of Bipartite Networks," Papers 1710.10143, arXiv.org.

    More about this item

    Keywords

    International Trade Network; Gravity Equation; Weighted Network Analysis; Topological Properties; Econophysics;

    JEL classification:

    • F10 - International Economics - - Trade - - - General
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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