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Global Economy Journal

The Official Publication of the International Trade and Finance Association

Ed. by Pelzman, Joseph

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Volume 14, Issue 2 (Jun 2014)


At the Core of the International Financial System

Valentina Feroldi / Edoardo Gaffeo
  • Corresponding author
  • Department of Economics and Management, University of Trento, Via Inama 5, Trento I-38100, Italy
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Published Online: 2014-06-17 | DOI: https://doi.org/10.1515/gej-2014-0006


This paper offers additional evidence on the structure of the international financial network as emerging from the Coordinated Portfolio Investment Survey (CPIS) dataset collected by the IMF. Making use of blockmodeling techniques which allow us to fit a given community partition to real data, we show that the system is characterized by the presence of a particular type of meso-scale structure known as core–periphery, in which a densely connected subset of nodes (core) coexists with a sparsely connected partition (periphery), while the members of the core act as intermediaries between members of the periphery. The composition of the core – whose constituents are identified as the set of systemically important international financial centers – is rather small and remains stable over time. In addition to very large economies playing host to well-known global financial centers, the core comprises several off-shore financial markets.

Keywords: international financial system; intermediation; network analysis

JEL Classification: F36; G15; E44


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About the article

Published Online: 2014-06-17

Published in Print: 2014-06-01

The list of offshore financial centers maintained by the IMF in its Assessment Program can be consulted at http://www.imf.org/external/NP/ofca/OFCA.aspx. Our choice to consider the Netherlands as an off-shore center will be motivated below.

The attribute of complexity is referred to a network which is neither regular nor purely random.

All these trends are further strengthened as one adds to the picture the issue of the global safe asset shortage discussed in Caballero (2006) and Bernanke et al. (2011).

For a survey of applications of network theory to finance see Allen and Babus (2009).

At least for scale-free networks with relatively small-scale exponents (Fricke, Finger, and Lux 2013).

For a survey on the literature on international financial centers exploring the intersections between economics and geography see Tschoegl (2000).

Centrality can be alternatively measured by the number of links terminating upon a node (in degree), by the distance from other nodes (closeness), or by assessing the degree by which a node lies on the shortest path between any two other nodes (betweenness).

Node strength is the total value of flows originating or terminating in a given node.

The prestige index measures the importance of a node by taking into account the importance of its neighbors.

Since the network is not self-referential, in what follows diagonal elements will be ignored.

The combinatorial optimization exercise for detecting a discrete core/periphery structure has been based on a genetic algorithm, see Borgatti and Everett (1999, 381).

The model has been developed to analyze instances of the German interbank market. Other applications to the Italian and the Dutch cases can be found in Fricke and Lux (2012) and van Lelyveld and in’t Veld (2012), respectively.

That is, at least one entry has to be non-zero in each column of CR and in each row or RR.

The data can be retrieved at http://cpis.imf.org/.

Each year a certain number of nodes are isolated. We retain them in the network if they contribute with a positive entry to the total adjacency matrix in at least one of the years under scrutiny. This allows us to take into account the evolution over time of international financial integration, and it facilitates intertemporal comparisons.

Their analysis covers the time span 2001–2010.

In absolute terms, the average number of core components are 66 and 44 for the discrete and the tiering models, respectively.

For ease of exposition, we present results for the tiering model only. The stability of the link structure for the discrete model is qualitatively similar.

Recall that the total error score should not be interpreted as a percentage, given that an error can occur either because of the absence of a link where the link is expected to exist or because of the presence of a link where the latter ought to be absent.

See e.g. Craig and von Peter (2014) and Fricke and Lux (2012).

Furthermore, some commentators have forcefully argued that during the last decades the favorable Dutch taxation regime has been extensively used by foreign corporations to implement sophisticated tax planning strategies, and that this has characterized the Dutch financial system as a conduit for financial flows to and from tax heavens (van Dijk, Weyzig, and Murphy 2006).

Citation Information: Global Economy Journal, ISSN (Online) 1524-5861, ISSN (Print) 2194-5659, DOI: https://doi.org/10.1515/gej-2014-0006.

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