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

Abstract

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.

arXiv comment20 pages, 6 figures

References in corpus (24)

• The Statistical Physics of Real-World Networks
• Fitness-dependent topological properties of the World Trade Web
• The Physics of Financial Networks
• Analytical maximum-likelihood method to detect patterns in real networks
• Maximum likelihood: extracting unbiased information from complex networks
• Early-warning signals of topological collapse in interbank networks
• Reciprocity of weighted networks
• Systemic risk analysis in reconstructed economic and financial networks
• Randomizing world trade. I. A binary network analysis
• Randomizing world trade. II. A weighted network analysis
• Cumulative effects of triadic closure and homophily in social networks
• Enhanced reconstruction of weighted networks from strengths and degrees
• Reconstructing the world trade multiplex: the role of intensive and extensive biases
• Deciphering the global organization of clustering in real complex networks
• Enhanced Gravity Model of trade: reconciling macroeconomic and network models
• Reconstructing networks
• Reconstructing firm-level interactions: the Dutch input-output network
• Relations between allometric scalings and fluctuations in complex systems: The case of Japanese firms
• A faster horse on a safer trail: generalized inference for the efficient reconstruction of weighted networks
• Stationarity, non-stationarity and early warning signals in economic networks
• Functional structure in production networks
• Distress propagation on production networks: Coarse-graining and modularity of linkages
• Reconciling econometrics with continuous maximum-entropy network models
• Deterministic, quenched and annealed parameter estimation for heterogeneous network models