Modeling supply-chain networks with firm-to-firm wire transfers. (15th March 2022)

• Record Type: Journal Article
• Authors: Silva, Thiago Christiano; Amancio, Diego Raphael; Tabak, Benjamin Miranda
• Is Part Of: Expert systems with applications. Volume 190(2022)
• Publication Date: 2022-03-15
• Subjects: Networks -- Firm trade networks -- Wire transfers -- Supply chains; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2021.116162
• Languages: English
• ISSNs: 0957-4174

Abstract

Abstract: We study a novel economic network (supply chain) comprised of wire transfers (electronic payment transactions) among the universe of firms in Brazil (6.2 million firms). We construct a directed and weighted network in which vertices represent cities and edges connote pairwise economic dependence between cities. Cities (vertices) represent the collection of all firms in that location, and links denote intercity wire transfers. We find a high degree of economic integration among cities in the trade network, consistent with the high degree of specialization across Brazilian cities. We identify cities with a dominant role as customers and suppliers to the entire supply chain using centrality network measures. The supply-chain network has a disassortative mixing pattern, which is explained by the heterogeneity in the size of Brazilian municipalities. We find that the supply-chain network becomes more disassortative during adverse times, such as the Brazilian recession in 2014 and the global financial crisis. We use entrepreneurship data and show that one potential driver of this change is the death of small firms, leading to a greater concentration of economic flows in larger centers. Our results suggest that adverse events significantly impact the supply-chain network with meaningful and heterogeneous economic consequences across municipalities. We run econometric exercises and find that courts' efficiency plays a dual role. From the customer perspective, it may reduce contractual frictions and increase economic transactions between cities. From the supplier perspective, cities that are central suppliers to the supply chain may use courts' inefficiency as a lawsuit barrier from their customers. Highlights: We study via machine learning firm-to-firm bilateral payments in the entire Brazilian economy. Following the Brazilian recession, we found deep structural changes in the complex network. Econometric analyzes showed that courts efficiency plays a dual role in the economic complex network.