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Dynamical topology of highly aggregated input-output networks

机译:高度聚合的输入输出网络的动态拓扑

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The paper studies topological properties of weighted directed graphs corresponding to highly aggregated macroeconomic input-output networks in Russia and the USA. As these graphs are complete or almost complete the study focuses on weight-sensitive characteristics of weighted directed networks. The analysis shows that while some generic features such as the fat-tailed nature of edge weight distribution, weighted fraction of triangles of different types and, to a certain extent, ranking with respect to PageRank and Hubs centrality are universal and do not change in time, the slopes of edge weight distributions, values of clustering coefficients and ranking of vertices with respect to certain centrality measures show visible evolution. The evolution of input-output matrices is also studied through analyzing the evolution of a distance between input-output matrices at varying time horizons. (C) 2018 Elsevier B.V. All rights reserved.
机译:本文研究加权指向图对应于俄罗斯和美国高度聚合的宏观经济投入输出网络的加权指导图的拓扑特性。 由于这些图形是完整的或几乎完成,研究重点是加权指向网络的体重敏感特性。 分析表明,虽然一些通用特征,如边缘重量分布的脂肪尾性,不同类型的三角形的加权分数,在一定程度上相对于PageRank和集线器中心排名是普遍的,并且不会随时间变化 ,边缘权重分布的斜率,聚类系数的值和相对于某些中心度量的顶点的排序显示了可见的演化。 还通过在变化时间范围内分析输入输出矩阵之间的距离的演变来研究输入输出矩阵的演变。 (c)2018年elestvier b.v.保留所有权利。

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