We use a model of proportionate growth to describe the dynamics of international trade flows. We provide an explanation to the fact that the extensive margin of trade account for a large fraction of the greater exports of large economies, as well as for a number of stylized facts described by the literature on trade networks such as the power-law distribution of connectivity and the fat tails displayed by the distribution of  the growth rates of trade flows. Hence, such a simple setup is able to capture the dynamics of very different economic variables, from firm size (as shown in the URLanization literature) to international trade flows (as documented here). Furthermore, we provide an additional element to the discussion on the relative ability of different international trade models to adequately match empirical regularities .
We develop a simple theoretical framework for the evolution of weighted network that is consistent with a number of stylized features of real-world data. In our framework, the Barabasi-Albert model of network evolution is extended as recently proposed by Stanley and colleagues in their work on complex system dynamics. Our model is verify by means of simulations and real world trade data. We show that the model correctly predicts the intensity and growth distribution of links, the size-variance relationships of the growth of link values, the relationship between the degree and strength of nodes, as well as the scale-free structure of the network .
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use a model of proportionate growth to describe the dynamics of international trade flows. We provide an explanation to the fact that the extensive margin of trade account for a large fraction of the greater exports of large economies, as well as for a number of stylized facts described by the literature on trade networks such as the power-law distribution of connectivity and
develop a simple theoretical framework for the evolution of weighted network that is consistent with a number of stylized features of real-world data. In our framework,
R
fat tails displayed by the distribution
Barabasi-Albert model of network evolution is extended as recently proposed by Stanley and colleagues in their work on complex system dynamics. Our model is verify by means of simulations and real world trade data. We show that the model correctly predicts the intensity and growth distribution of links, the size-variance relationships of the growth
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link values,
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growth rates of trade flows. Hence, such a simple setup is able to capture the dynamics of very different economic variables, from firm size (as shown in the URLanization literature) to international trade flows (as documented here). Furthermore, we provide an additional element to the discussion on the relative ability of different international trade models to adequately match empirical regularities
relationship between the degree and strength of nodes, as well as the scale-free structure of the network