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Complex Networks and Dynamics pp 173–193Cite as

The Empirics of Macroeconomic Networks: A Critical Review

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Part of the book series: Lecture Notes in Economics and Mathematical Systems ((LNE,volume 683))

Abstract

This chapter critically surveys the recent empirical literature applying complex-network techniques to the study of macroeconomic dynamics. We focus on three important macroeconomic networks: international trade, finance and migration/mobility. We discuss both the empirical evidence on the topological properties of these networks and econometric works that identify the impact of network properties on macroeconomic dynamics. Results indicate that a detailed knowledge of macroeconomic networks is necessary to better understand the dynamics of country income, growth and productivity, as well as the diffusion of crises.

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Notes

  1. 1.

    See Schweitzer et al. (2009), De Martí and Zenou (2009), Jackson (2010), Easley and Kleinberg (2010), and Jackson and Zenou (2015).

  2. 2.

    Cf., among others, May et al. (2008), Guerrero and Axtell (2013), and Saito et al. (2007).

  3. 3.

    A parallel line of research, which we will not discuss here, has explored infrastructure networks connecting world countries, which facilitate how people and goods move across space and borders (e.g., air, cargo and maritime transportation networks; cf. Barrat et al. 2004; Hua and Zhu 2009; Kaluza et al. 2011; Woolley-Meza et al. 2011).

  4. 4.

    Of course, the number of world countries to be considered in the analysis at time t may depend not only on those actually existing at t but also on data availability at that period of time.

  5. 5.

    Due to data availability, misreporting and the presence of zero flows, C t may also depend, in principle, on the type of interaction ι. In what follows, we will focus on cases when one restricts the analysis on the minimal set of countries present in all interaction layers, so that C t(ι) = C t.

  6. 6.

    By “second wave of globalization” we mean the period from 1945 onwards, as opposed to the “first wave of globalization” (1800–1914). The two waves are separated by a slump in international trade occurred between the two world Wars (Baldwin and Martin 1999).

  7. 7.

    World Development Indicators Online (WDI) database, see http://data.worldbank.org/data-catalog/world-development-indicators.

  8. 8.

    Quantitative approaches to the study of trade in terms of networks have been pioneered in sociology and political sciences. For instance, the seminal paper by Snyder and Kick (1979) triggered a fruitful literature mostly aimed at testing some flavor of “world system” or “dependency” theories using social-network analysis techniques, see e.g. Nemeth and Smith (1985), Sacks et al. (2001), Breiger (1981), Smith and White (1992), Kim and Shin (2002) and Mahutga (2006), and the discussion in Fagiolo et al. (2010).

  9. 9.

    See for example COMTRADE (comtrade.un.org), the BACI dataset at CEPII (cepii.fr) or data on trade in goods and services at UNCTAD (unctadstat.unctad.org). Additional data are available from individual researchers, e.g. Andrew Rose (http://faculty.haas.berkeley.edu/arose/), Kristian Gleditsch (privatewww.essex.ac.uk/~ksg/), Robert Feenstra (cid.econ.ucdavis.edu), and Arvind Subramanian and Shang-Jin Wei (users.nber.org/~wei/data.html), among others. See also De Benedictis et al. (2014) for a tutorial-like presentation of the main properties of the ITN using the BACI dataset. See also the WIOD dataset (wiod.org), which provides time-series data of world input-output tables for 40 countries worldwide.

  10. 10.

    See, however, Egger et al. (2016) for a recent attempt bridging trade in goods and trade in services.

  11. 11.

    See wto.org/english/news_e/pres14_e/pr721_e.htm.

  12. 12.

    To this figure, one should also add the value of total foreign-direct investments (FDIs) flows, which in 2012 reached US$ 1.4 trillion, cf. oecd.org.

  13. 13.

    Due to space constraints and the focus on macroeconomic relations, we cannot survey here the extremely interesting and influential literature on micro and meso financial networks, especially the contributions addressing systemic risk (Cf. e.g. the work of Stefano Battiston and co-authors: See for instance Battiston et al. 2012a,b). The interested reader is referred to the reviews by Hasman (2013) and Chinazzi and Fagiolo (2013).

  14. 14.

    FDIs are another important channel of interaction between world countries. Typically a large part of cross-border FDIs are done in terms of direct M&A between firms of two countries. Using alternative data sources (e.g., Thomson Reuters Mergers and Acquisitions database, see http://thomsonreuters.com/en/products-services/financial/hedge-funds/mergers-and-acquisitions.html), one may build, for each given time window, an international M&A network where nodes are countries and (direct) links represent acquirer-target M&A operations (in number of in total value). Interesting issues that can be addressed with this network concern, e.g., the geographical localization of clusters of countries engaged in M&A activities and the persistency over time of investment flows.

  15. 15.

    See http://publications.iom.int/bookstore/free/WMR_2010_ENGLISH.pdf.

  16. 16.

    Another subtle and potentially important issue arising in dealing with econometric models involving networks is the existing interdependency between dyadic observations. This might bias results in e.g. gravity-like estimations due to the omissions of higher-level correlation between triads and, more generally, cliques; see, e.g., Ward et al. (2013).

  17. 17.

    See also Foti et al. (2013). They study a simple model of diffusion where, after the system is shocked, a local rebalancing of supply and demand is assumed to occur in order to mitigate the effects of the shock.

  18. 18.

    This parallels trade openness, defined as the sum of import and exports divided by country GDP.

  19. 19.

    Of course here causality is exogenously assumed by means of theoretical arguments, and not tested econometrically.

  20. 20.

    See Sgrignoli et al. (2015) for a complementary analysis that explores similar issues using a product-specific trade perspective.

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Authors and Affiliations

  1. Istituto di Economia, Scuola Superiore Sant’Anna, Piazza Martiri della Libertà, 33, 56127, Pisa, Italy

    Giorgio Fagiolo

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  1. Giorgio Fagiolo
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Editors and Affiliations

  1. Department of Law, University of Naples "Federico II", Naples, Italy

    Pasquale Commendatore

  2. Faculty of Economics, UNED, Madrid, Spain

    Mariano Matilla-García

  3. Faculty of Physics, University of Santiago de Compostela, Santiago de Compostela, Spain

    Luis M. Varela

  4. Department of Applied Mathematics, Technical University of Cartagena, Cartagena, Spain

    Jose S. Cánovas

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Fagiolo, G. (2016). The Empirics of Macroeconomic Networks: A Critical Review. In: Commendatore, P., Matilla-García, M., Varela, L., Cánovas, J. (eds) Complex Networks and Dynamics. Lecture Notes in Economics and Mathematical Systems, vol 683. Springer, Cham. https://doi.org/10.1007/978-3-319-40803-3_7

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