Global networks of trade and bits

Abstract

Considerable efforts have been made in recent years to produce detailed topologies of the Internet. Although Internet topology data have been brought to the attention of a wide and somewhat diverse audience of scholars, so far they have been overlooked by economists. In this paper, we suggest that such data could be effectively treated as a proxy to characterize the size of the "digital economy" at country level and outsourcing: thus, we analyse the topological structure of the network of trade in digital services (trade in bits) and compare it with that of the more traditional flow of manufactured goods across countries. To perform meaningful comparisons across networks with different characteristics, we define a stochastic benchmark for the number of connections among each country-pair, based on hypergeometric distribution. Original data are thus filtered by means of different thresholds, so that we only focus on the strongest links, i.e., statistically significant links. We find that trade in bits displays a sparser and less hierarchical network structure, which is more similar to trade in high-skill manufactured goods than total trade. Lastly, distance plays a more prominent role in shaping the network of international trade in physical goods than trade in digital services.JEL Codes: F14, L86, O33

World Input-Output Network

“…As mentioned in Section I, the complex networks approach has been widely used in economics and finance in recent years [16][17][18][19][20][21]. Designed to keep track of the inter-industrial relationships, the input-output system is an ideal test bed for network science.…”

“…However, to the best of our knowledge, our paper is the first attempt to explore the MRIO tables from a networks perspective, even though there have been some networks studies of the input-output tables at the national level and for selected countries [10][11][12].Complex networks are a modern way to characterize mathematically a series of different systems in the shape of subunits (nodes) connected by their interaction (edges) [13,14]. Such modeling has been proved to be fruitful for the description of a variety of different phenomena ranging from biology [15] to economics [16][17][18][19][20] and finance [21]. Here we move forward by considering the global MRIO system as a world input-output network (WION), where the nodes are the individual industries in different economies and the edges are the monetary goods flows 3 between industries, similarly to what have been done recently by Acemoglu, Carvalho, Ozdaglar and Tahbaz-Salehi for the US economy only [22].…”

The indirect effects of foreign direct investment on trade: A network perspective

“…The spatial econometrics result is available upon request. Tajoli, 2011;Fagiolo, Reyes, & Schiavo, 2009;Frankel & Rose, 2002;Garlaschelli & Loffredo, 2005;Glick & Rose, 2002;Reyes, Wooster, & Shirrell, 2014;Serrano & Bogun a, 2003) and corporate control (Altomonte & Rungi, 2013;Head & Ries, 2008;Vitali, Glattfelder, & Battiston, 2011) can be considered as networks and their network properties can be used to understand other economic variables (Fagiolo & Mastrorillo, 2014;Ferrier, Reyes, & Zhu, 2016;Riccaboni, Rossi, & Schiavo, 2012;Schiavo, Reyes, & Fagiolo, 2010;Sgrignoli, Metulini, Schiavo, & Riccaboni, 2015). For the world system of either trade or corporate control, we can construct a network, where we identify countries as nodes and interaction channels between them as edges.…”

Big hits, export concentration and volatility

“…This feature is found to characterise many real-world applications besides trade, such as the internet(Faloutsos et al 1999;Riccaboni et al 2013), world-wide air transportation(Guimera et al 2005), migration(Sgrignoli et al 2015), mobile communications(Onnela et al 2007) and interbank payments(Soramäki et al 2007). …”