Approximations for time-dependent distributions in Markovian fluid models

In this paper we study the distribution of the level at time $\theta$ of Markovian fluid queues and Markovian continuous time random walks, the maximum (and minimum) level over $[0,\theta]$, and their joint distributions. We approximate $\theta$ by a random variable $T$ with Erlang distribution and we use an alternative way, with respect to the usual Laplace transform approach, to compute the distributions. We present probabilistic interpretation of the equations and provide a numerical illustration

Scale-Free Networks in International Trade

The paper analyzes the network structure of international trade. Adapting a network approach developed in the physical sciences, we propose that international trade functions like a scale-free network. For each commodity group we calculate a characteristic parameter which reflects the structure of its trading network. We then insert this variable into an expanded gravity model to explore the effect of the network structure on the value of bilateral trade. The estimation suggests that, inter alia, globalization has reduced the value of trade per product group.Networks, International trade, Gravity model

The World-Trade Web: Topological Properties, Dynamics, and Evolution

This paper studies the statistical properties of the web of import-export relationships among world countries using a weighted-network approach. We analyze how the distributions of the most important network statistics measuring connectivity, assortativity, clustering and centrality have co-evolved over time. We show that all node-statistic distributions and their correlation structure have remained surprisingly stable in the last 20 years -- and are likely to do so in the future. Conversely, the distribution of (positive) link weights is slowly moving from a log-normal density towards a power law. We also characterize the autoregressive properties of network-statistics dynamics. We find that network-statistics growth rates are well-proxied by fat-tailed densities like the Laplace or the asymmetric exponential-power. Finally, we find that all our results are reasonably robust to a few alternative, economically-meaningful, weighting schemes.Comment: 44 pages, 39 eps figure

The Heckscher-Ohlin Model and the Network Structure of International Trade

This paper estimates for 28 product groups a characteristic parameter that reflects the topological structure of its trading network. Using these estimates, it then describes how the structure of international trade has evolved during the 1980-2000 period. Thereafter, it demonstrates the importance of networks in international trade by explicitly accounting for their scaling properties when testing the prediction of the Heckscher-Ohlin model that factor endowment differentials determine bilateral trade flows. The results suggest that differences in factor endowments increase bilateral trade in goods that are traded in "dispersed" networks. For goods that are traded in "concentrated" networks, factor endowment differentials are less important.Networks, international trade, gravity model

Mixed Tempered Stable distribution

In this paper we introduce a new parametric distribution, the Mixed Tempered Stable. It has the same structure of the Normal Variance Mean Mixtures but the normality assumption leaves place to a semi-heavy tailed distribution. We show that, by choosing appropriately the parameters of the distribution and under the concrete specification of the mixing random variable, it is possible to obtain some well-known distributions as special cases. We employ the Mixed Tempered Stable distribution which has many attractive features for modeling univariate returns. Our results suggest that it is enough flexible to accomodate different density shapes. Furthermore, the analysis applied to statistical time series shows that our approach provides a better fit than competing distributions that are common in the practice of finance

The Structure and Growth of International Trade

The paper develops a model of proportionate growth to describe the dynamics of international trade flows. We show that a large number of the empirical regularities characterizing international trade -such as the fraction of zero trade flows across pairs of countries, the positive relationship between inten- sive and extensive margins, the high concentration of trade with respect to both products and destinations, the core-periphery structure of exchanges- are well explained by this simple stochastic setup. This helps us to distinguish among economically relevant regularities and those simply resulting from the mechanical interactions among agents. Furthermore, our model can be used to describe the process of `self-discovery' that lie at the foundations of suc- cessful export-led growth and is thought to play a crucial role in the process of economic development. Our model correctly predicts that large export flows are rare events, as pointed out in the empirical literature: yet, countries char- acterized by large `discovery' efforts are much more likely to draw a `big hit' due to the (very skewed) shape of the distribution of bilateral export flows.international trade, development, weighted networks, proportionate growth, industrial policy