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Trade networks and economic fluctuations in Asian countries

机译:亚洲国家的贸易网络​​和经济波动

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The paper presents a new methodology, based on tensor decomposition, to map dynamic trade networks and to assess its strength in forecasting economic fluctuations at different periods of time in Asia. Using the monthly merchandise import and export data across 33 Asian economies, together with the US, EU and UK, we detect the community structure of the evolving network and we identify clusters and central nodes inside each of them. Our findings show that data are well represented by two communities, in which People's Republic of China and Japan play the major role. We then analyze the synchronisation between GDP growth and trade. Furthermore we apply our model to the prediction of economic fluctuations. Our findings show that the model leads to an increase in predictive accuracy, as higher order interactions between countries are taken into account.
机译:本文提出了一种基于张量分解的新方法,可绘制动态贸易网络并评估其预测亚洲不同时期经济波动的能力。通过使用33个亚洲经济体以及美国,欧盟和英国的月度商品进出口数据,我们可以检测到不断发展的网络的社区结构,并确定其中的集群和中心节点。我们的研究结果表明,数据由两个社区很好地代表,其中中华人民共和国和日本在其中发挥了主要作用。然后,我们分析GDP增长与贸易之间的同步。此外,我们将我们的模型应用于经济波动的预测。我们的发现表明,由于考虑到国家之间的更高层次的互动,该模型可以提高预测的准确性。

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