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We analyze export data aggregated at world global level of 219 classes ofproducts over a period of 39 years. Our main goal is to set up a dynamicalmodel to identify and quantify plausible mechanisms by which the evolutions ofthe various exports affect each other. This is pursued through a stochasticdifferential description, partly inspired by approaches used in populationdynamics or directed polymers in random media. We outline a complex network oftransfer rates which describes how resources are shifted between differentproduct classes, and determines how casual favorable conditions for one exportcan spread to the other ones. A calibration procedure allows to fit four freemodel-parameters such that the dynamical evolution becomes consistent with theaverage growth, the fluctuations, and the ranking of the export values observedin real data. Growth crucially depends on the balance between maintaining andshifting resources to different exports, like in an explore-exploit problem.Remarkably, the calibrated parameters warrant a close-to-maximum growth rateunder the transient conditions realized in the period covered by data, implyingan optimal self organization of the global export. According to the model,major structural changes in the global economy take tens of years.

Export dynamics as an optimal growth problem in the network of global economy