资源环境科技发展态势分析平台

We present a new methodology, based on tensor decomposition, to map dynamic trade networks and assess their strength in spreading economic fluctuations at different periods of time in Asia. Using monthly merchandise import and export data across 33 Asian economies, together with the United Sates, the European Union, and the United Kingdom, we detect the modularity structure of the evolving network and we identify communities and central nodes inside each of them. Our findings show that data are well represented by two communities, in which the People's Republic of China and Japan play the major role. We then analyze the synchronization between GDP growth and trade, and 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.

WORKING PAPER NO: 832