Keywords: Complex networks, Information theory and computation.
Recent crises have shown that the knowledge of the structure of input–output networks, at the frm level, is crucial when studying economic resilience from the microscopic point of view of frms that try to rewire their connections under supply and demand constraints. Unfortunately, empirical inter-frm network data are protected by confdentiality, hence rarely accessible. The available methods for network reconstruction from partial information treat all pairs of nodes as potentially interacting, thereby overestimating the rewiring capabilities of the system and the implied resilience. Here, we use two big data sets of transactions in the Netherlands to represent a large portion of the Dutch inter-frm network and document its properties. We, then, introduce a generalized maximum-entropy reconstruction method that preserves the production function of each frm in the data, i.e. the input and output fows of each node for each product type. We confrm that the new method becomes increasingly more reliable in reconstructing the empirical network as a fner product resolution is considered and can, therefore, be used as a realistic generative model of inter-frm networks with fne production constraints. Moreover, the likelihood of the model directly enumerates the number of alternative network confgurations that leave each frm in its current production state, thereby estimating the reduction in the rewiring capability of the system implied by the observed input– output constraints.
Ialongo, L. N., de Valk, C., Marchese, E., Jansen, F., Zmarrou, H., Squartini, T., & Garlaschelli, D. (2022). Reconstructing firm-level interactions in the Dutch input–output network from production constraints. Scientific reports, 12(1), 1-12. https://link.springer.com/content/pdf/10.1038/s41598-022-13996-3.pdf