Most national economies are linked by international trade. Consequently, economic globalization forms a massive and complex economic network with strong links, that is, interactions arising from increasing trade. Various interesting collective motions are expected to emerge from strong economic interactions in a global economy under trade liberalization. Among the various economic collective motions, economic crises are our most intriguing problem. In our previous studies, we have revealed that the Kuramoto's coupled limit-cycle oscillator model and the Ising-like spin model on networks are invaluable tools for characterizing the economic crises. In this study, we develop a mathematical theory to describe an interacting agent model that derives the Kuramoto model and the Ising-like spin model by using appropriate approximations. Our interacting agent model suggests phase synchronization and spin ordering during economic crises. We confirm the emergence of the phase synchronization and spin ordering during economic crises by analyzing various economic time series data. We also develop a network reconstruction model based on entropy maximization that considers the sparsity of the network. Here network reconstruction means estimating a network's adjacency matrix from a node's local information. The interbank network is reconstructed using the developed model, and a comparison is made of the reconstructed network with the actual data. We successfully reproduce the interbank network and the known stylized facts. In addition, the exogenous shock acting on an industry community in a supply chain network and financial sector are estimated. Estimation of exogenous shocks acting on communities of in the real economy in the supply chain network provide evidence of the channels of distress propagating from the financial sector to the real economy through the supply chain network.
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