Human-Mobility Networks, Country Income, and Labor Productivity

Abstract

This paper asks whether the level of integration of world countries in the international network of temporary human mobility can explain differences in their per-capita income and labor productivity. We disentangle the role played by global country centrality in the network from traditional openness measures, which only account for local, nearestneighbor linkages through which ideas and knowledge can flow. Using 1995-2010 data, we show that global country centrality in the temporary human-mobility network enhances both per-capita income and labor productivity. Our results hold cross-sectionally, as well as in a dynamic-panel estimation, and take into account potential endogeneity issues. Our findings imply that how close a country is to the theoretical technological frontier, depends not only on how much she is open to temporary human mobility, but mostly on whether she is embedded in a web of relationships connecting her with other influential partners in the network. Our exercises also suggest that most of the gain in income and productivity can be attained if country centrality in the network comes mostly from influential partners that lie not too far away from, but neither too close to them in the network.

A Network Analysis of the Volatility of High Dimensional Financial Series

“…The study of networks as complex systems has been the subject of intensive research in recent years, both in the physics and statistics communities (see, for example, Kolaczyk, 2009, for a review of the main models, methods, and results). Typically, the datasets considered in that literature exhibit a "natural" or pre-specified network structure, as, for example, world trade fluxes (Serrano and Boguñá, 2003;Barigozzi et al, 2010), co-authorship relations (Newman, 2001), power grids (Watts and Strogatz, 1998), social individual relationships (Zachary, 1977), fluxes of migrants (Fagiolo and Santoni, 2015), or political weblog data (Adamic and Glance, 2005). In all those studies, the network structure (as a collection of vertices and edges) is known, and pre-exists the observations.…”

Current account and international networks

“…In the analysis that follows, I consider both exports and imports for computation of ITN centrality measures and both financial outflows and inflows for computation of IFN centrality measures. In this way, the constructed centrality indicators are more in line with trade and financial openness indicators, which take into account both inflows and outflows (see Fagiolo & Santoni, 2015).…”

“…There is a number of network centrality indicators used for the analysis of international trade and financial networks (see Aller et al., 2015; Chinazzi, Fagiolo, Reyes, & Schiavo, 2013; De Benedictis & Tajoli, 2011; Fagiolo, Reyes, & Schiavo, 2009, 2010; Fagiolo & Santoni, 2015; Minoiu & Reyes, 2013). Given the importance of the intercountry interactions for determination of the current account, I consider the global centrality indicators: closeness, betweenness, and eigenvector centrality.…”

Country centrality in the international multiplex network

“…However, there are some international networks in which directed edges represent relationships other than monetary exchanges, such as the networks of migration and human mobility (Sgrignoli et al 2015;Fagiolo and Santoni 2016;Fagiolo and Santoni 2015;Fagiolo and Mastrorillo 2014;Riccaboni et al 2013).…”