Quantifying cascading effects in trade networks

Stochastic events can affect the ability of a country to produce and export natural resources such as food. When exposed to such events, an importing country will face a deficit on the expected trade of a product and turn to another trading partner to supply its demand. This simple mechanism can therefore couple oscillations on resource exploitation and consumption in far away places of the planet, a phenomenon theorized as telecouplings1. Here we use montly time series of salmon trade to recostruct a network of potential telecoupling effects, this is when the export dynamics of a country \(c_i\) to \(c_j\) causally affects the dynamics of exports from \(c_k\) to \(c_j\). Our results show that non-linear causal effects do not spread more than few degrees of separation in the trade network; and in fact less than 20 time series out of 402 mapped links in the network have a forecasting skill higher than 20% on secondary links. We offer empirical evidence of telecoupling in the salmon trade network as well as an innovative methodological approach to assess causality of non-linear dynamics in networked systems.