eprintid: 2696
rev_number: 8
eprint_status: archive
userid: 69
dir: disk0/00/00/26/96
datestamp: 2015-05-21 09:39:15
lastmod: 2015-05-21 09:39:15
status_changed: 2015-05-21 09:39:15
type: article
metadata_visibility: show
creators_name: Riccaboni, Massimo
creators_name: Schiavo, Stefano
creators_id: massimo.riccaboni@imtlucca.it
creators_id: 
title: Stochastic trade networks
ispublished: pub
subjects: HB
subjects: HF
divisions: EIC
full_text_status: none
keywords: International trade, Networks, Preferential attachment, Urn models, Proportional growth
note: Available online June 2014
abstract: This paper develops a simple network model to describe the dynamics of international trade flows. The result is achieved by means of the combination of two mechanisms of proportional growth: the first determines the formation of trade links (intensive margin of trade) and the second governs trade intensity (extensive margin of trade). With respect to recent network models of trade, our approach better fits the numbers of zeros and the degree distribution at different levels of aggregation from firms to national economies. Furthermore, we match a number of additional empirical regularities such as the high concentration of trade with respect to both products and destinations, and the relationship between node degree and node strength. These findings suggest that stylized facts are strongly interconnected across different levels of aggregation, so that a unifying explanation is called for. Our network model can be employed as a useful stochastic benchmark, similar to a generalized gravity model for both trade margins. 
date: 2014-12
date_type: published
publication: Journal of Complex Networks
volume: 2
number: 4
publisher: Oxford University Press
pagerange: 537-556
id_number: 10.1093/comnet/cnu025
refereed: TRUE
issn: 2051-1310
official_url: http://comnet.oxfordjournals.org/content/2/4/537.abstract
citation:   Riccaboni, Massimo and Schiavo, Stefano  Stochastic trade networks.  Journal of Complex Networks, 2 (4).  pp. 537-556.  ISSN 2051-1310      (2014)