10 research outputs found
Structure and Evolution of the World Trade Network
The \emph{World Trade Web} (WTW), the network defined by the international
import/export trade relationships, has been recently shown to display some
important topological properties which are tightly related to the Gross
Domestic Product of world countries. While our previous analysis focused on the
static, undirected version of the WTW, here we address its full evolving,
directed description. This is accomplished by exploiting the peculiar
reciprocity structure of the WTW to recover the directed nature of
international trade channels, and by studying the temporal dependence of the
parameters describing the WTW topology.Comment: Proceedings of the "First Bonzenfreies Colloquium on Market Dynamics
and Quantitative Economics", Alessandria (ITALY) September 9-10, 2004. One of
the three awarded talk
Interplay between topology and dynamics in the World Trade Web
We present an empirical analysis of the network formed by the trade
relationships between all world countries, or World Trade Web (WTW). Each
(directed) link is weighted by the amount of wealth flowing between two
countries, and each country is characterized by the value of its Gross Domestic
Product (GDP). By analysing a set of year-by-year data covering the time
interval 1950-2000, we show that the dynamics of all GDP values and the
evolution of the WTW (trade flow and topology) are tightly coupled. The
probability that two countries are connected depends on their GDP values,
supporting recent theoretical models relating network topology to the presence
of a `hidden' variable (or fitness). On the other hand, the topology is shown
to determine the GDP values due to the exchange between countries. This leads
us to a new framework where the fitness value is a dynamical variable
determining, and at the same time depending on, network topology in a
continuous feedback.Comment: Proceedings of the 5th conference on Applications of Physics in
Financial Analysis (APFA5), 29 June - 1 July 2006, Torino (ITALY
The entropy of randomized network ensembles
Randomized network ensembles are the null models of real networks and are
extensivelly used to compare a real system to a null hypothesis. In this paper
we study network ensembles with the same degree distribution, the same
degree-correlations or the same community structure of any given real network.
We characterize these randomized network ensembles by their entropy, i.e. the
normalized logarithm of the total number of networks which are part of these
ensembles.
We estimate the entropy of randomized ensembles starting from a large set of
real directed and undirected networks. We propose entropy as an indicator to
assess the role of each structural feature in a given real network.We observe
that the ensembles with fixed scale-free degree distribution have smaller
entropy than the ensembles with homogeneous degree distribution indicating a
higher level of order in scale-free networks.Comment: (6 pages,1 figure,2 tables
Unbiased information extraction from complex networks by means of the maximum likelihood approach
Fitness-dependent topological properties of the World Trade Web
Among the proposed network models, the hidden variable (or good get richer) one is particularly interesting, even if an explicit empirical test of its hypotheses has not yet been performed on a real network. Here we provide the first empirical test of this mechanism on the world trade web, the network defined by the trade relationships between world countries. We find that the power-law distributed gross domestic product can be successfully identified with the hidden variable (or fitness) determining the topology of the world trade web: all previously studied properties up to third-order correlation structure (degree distribution, degree correlations and hierarchy) are found to be in excellent agreement with the predictions of the model. The choice of the connection probability is such that all realizations of the network with the same degree sequence are equiprobable.
Structure and Evolution of the World Trade Network
The \emph{World Trade Web} (WTW), the network defined by the international import/export trade relationships, has been recently shown to display some important topological properties which are tightly related to the Gross Domestic Product of world countries. While our previous analysis focused on the static, undirected version of the WTW, here we address its full evolving, directed description. This is accomplished by exploiting the peculiar reciprocity structure of the WTW to recover the directed nature of international trade channels, and by studying the temporal dependence of the parameters describing the WTW topology.
Interplay between topology and dynamics in the World Trade Web
We present an empirical analysis of the network formed by the trade relationships between all world countries, or World Trade Web (WTW). Each (directed) link is weighted by the amount of wealth flowing between two countries, and each country is characterized by the value of its Gross Domestic Product (GDP). By analysing a set of year-by-year data covering the time interval 1950-2000, we show that the dynamics of all GDP values and the evolution of the WTW (trade flow and topology) are tightly coupled. The probability that two countries are connected depends on their GDP values, supporting recent theoretical models relating network topology to the presence of a `hidden' variable (or fitness). On the other hand, the topology is shown to determine the GDP values due to the exchange between countries. This leads us to a new framework where the fitness value is a dynamical variable determining, and at the same time depending on, network topology in a continuous feedback.