The role of distances in the World Trade Web
Francesco Picciolo,
Tiziano Squartini,
Franco Ruzzenenti,
Riccardo Basosi and
Diego Garlaschelli
Papers from arXiv.org
Abstract:
In the economic literature, geographic distances are considered fundamental factors to be included in any theoretical model whose aim is the quantification of the trade between countries. Quantitatively, distances enter into the so-called gravity models that successfully predict the weight of non-zero trade flows. However, it has been recently shown that gravity models fail to reproduce the binary topology of the World Trade Web. In this paper a different approach is presented: the formalism of exponential random graphs is used and the distances are treated as constraints, to be imposed on a previously chosen ensemble of graphs. Then, the information encoded in the geographical distances is used to explain the binary structure of the World Trade Web, by testing it on the degree-degree correlations and the reciprocity structure. This leads to the definition of a novel null model that combines spatial and non-spatial effects. The effectiveness of spatial constraints is compared to that of nonspatial ones by means of the Akaike Information Criterion and the Bayesian Information Criterion. Even if it is commonly believed that the World Trade Web is strongly dependent on the distances, what emerges from our analysis is that distances do not play a crucial role in shaping the World Trade Web binary structure and that the information encoded into the reciprocity is far more useful in explaining the observed patterns.
Date: 2012-10, Revised 2012-10
New Economics Papers: this item is included in nep-geo and nep-net
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)
Published in in Proceedings of the Eighth International Conference on Signal-Image Technology & Internet-Based Systems (SITIS 2012), pp. 784-792 (edited by IEEE) (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1210.3269
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