  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.
