Commodity-specific triads in the Dutch inter-industry production network

• Published in: Scientific reports Vol. 14; no. 1; pp. 3625 - 18
• Main Authors: Di Vece, Marzio, Pijpers, Frank P., Garlaschelli, Diego
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 13-02-2024; Nature Publishing Group; Nature Portfolio
• Subjects: 639/705/531; 639/766/259; 639/766/530/2801; Commodities; Datasets; Entropy; Heterogeneity; Humanities and Social Sciences; multidisciplinary; Science; Science (multidisciplinary); Suppliers
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-024-53655-3

Triadic motifs are the smallest building blocks of higher-order interactions in complex networks and can be detected as over-occurrences with respect to null models with only pair-wise interactions. Recently, the motif structure of production networks has attracted attention in light of its possible role in the propagation of economic shocks. However, its characterization at the level of individual commodities is still poorly understood. Here we analyze both binary and weighted triadic motifs in the Dutch inter-industry production network disaggregated at the level of 187 commodity groups, which Statistics Netherlands reconstructed from National Accounts registers, surveys and known empirical data. We introduce appropriate null models that filter out node heterogeneity and the strong effects of link reciprocity and find that, while the aggregate network that overlays all products is characterized by a multitude of triadic motifs, most single-product layers feature no significant motif, and roughly 85% of the layers feature only two motifs or less. This result paves the way for identifying a simple ‘triadic fingerprint’ of each commodity and for reconstructing most product-specific networks from partial information in a pairwise fashion by controlling for their reciprocity structure. We discuss how these results can help statistical bureaus identify fine-grained information in structural analyses of interest for policymakers.