Title
The Role of Distances in the World Trade Web
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.
Year
DOI
Venue
2012
10.1109/SITIS.2012.118
signal-image technology and internet-based systems
Field
DocType
Volume
Econometrics,Combinatorics,Bayesian information criterion,Random graph,Akaike information criterion,Computer science,Reciprocity (social psychology),Null model,Formalism (philosophy),Globalization,Binary number
Journal
abs/1210.3269
ISSN
Citations 
PageRank 
in Proceedings of the Eighth International Conference on Signal-Image Technology & Internet-Based Systems (SITIS 2012), pp. 784-792 (edited by IEEE) (2013)
2
0.46
References 
Authors
0
5
Name
Order
Citations
PageRank
Francesco Picciolo1313.55
Tiziano Squartini26711.86
Franco Ruzzenenti3385.36
Riccardo Basosi4183.67
Diego Garlaschelli59018.49