Trade Integration and Trade Imbalances in the European Union: A Network Perspective

We study the ever more integrated and ever more unbalanced trade relationships between European countries. To better capture the complexity of economic networks, we propose two global measures that assess the trade integration and the trade imbalances of the European countries. These measures are the network (or indirect) counterparts to traditional (or direct) measures such as the trade-to-GDP (Gross Domestic Product) and trade deficit-to-GDP ratios. Our indirect tools account for the European inter-country trade structure and follow (i) a decomposition of the global trade flow into elementary flows that highlight the long-range dependencies between exporting and importing economies and (ii) the commute-time distance for trade integration, which measures the impact of a perturbation in the economy of a country on another country, possibly through intermediate partners by domino effect. Our application addresses the impact of the launch of the Euro. We find that the indirect imbalance measures better identify the countries ultimately bearing deficits and surpluses, by neutralizing the impact of trade transit countries, such as the Netherlands. Among others, we find that ultimate surpluses of Germany are quite concentrated in only three partners. We also show that for some countries, the direct and indirect measures of trade integration diverge, thereby revealing that these countries (e.g. Greece and Portugal) trade to a smaller extent with countries considered as central in the European Union network.

[1]  Walter E. Beyeler,et al.  The topology of interbank payment flows , 2007 .

[2]  Charles M. Grinstead,et al.  Introduction to probability , 1999, Statistics for the Behavioural Sciences.

[3]  Philippe Chevalier,et al.  Pooling in manufacturing: do opposites attract? , 2013 .

[4]  H. L. Le Roy,et al.  Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability; Vol. IV , 1969 .

[5]  G. Crooks On Measures of Entropy and Information , 2015 .

[6]  A. Rényi On Measures of Entropy and Information , 1961 .

[7]  G. Fagiolo,et al.  The evolution of the world trade web: a weighted-network analysis , 2008 .

[8]  Giorgio Fagiolo,et al.  World-trade web: topological properties, dynamics, and evolution. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.

[9]  Sergey Brin,et al.  The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.

[10]  D. Garlaschelli,et al.  Structure and evolution of the world trade network , 2005, physics/0502066.

[11]  Giorgio Fagiolo,et al.  Assessing the Evolution of International Economic Integration Using Random Walk Betweenness Centrality: the Cases of East Asia and Latin America , 2008, Adv. Complex Syst..

[12]  Koen Decancq,et al.  What do normative indices of multidimensional inequality really measure , 2015 .

[13]  Y. Koren,et al.  Drawing graphs by eigenvectors: theory and practice , 2005 .

[14]  Zhi-Li Zhang,et al.  Commute Times for a Directed Graph using an Asymmetric Laplacian , 2011 .

[15]  Pierre Pestieau,et al.  FGT Poverty Measures and the Mortality Paradox: Theory and Evidence , 2013 .

[16]  R. Baldwin,et al.  The Euro's Trade Effects , 2006, SSRN Electronic Journal.

[17]  Giorgio Fagiolo,et al.  Global Trade Imbalances: A Network Approach , 2013 .

[18]  César A. Hidalgo,et al.  The building blocks of economic complexity , 2009, Proceedings of the National Academy of Sciences.

[19]  W. Bossert,et al.  The Measurement of Diversity , 2001 .

[20]  Luc BAUWENS,et al.  Handbook of Volatility Models and Their Applications , 2012 .

[21]  John N. Tsitsiklis,et al.  Introduction to Probability , 2002 .

[22]  Giorgio Fagiolo,et al.  Global Trade Imbalances: A Network Approach , 2013, Adv. Complex Syst..

[23]  K. Kaski,et al.  The International Trade Network: weighted network analysis and modelling , 2007, 0707.4343.

[24]  Andrea Fracasso,et al.  Global imbalances, exchange rates adjustment and the crisis: Implications from network analysis , 2009 .

[25]  Michael W. Deem,et al.  Structure and Response in the World Trade Network , 2010, Physical review letters.

[26]  Kenneth M. Hall An r-Dimensional Quadratic Placement Algorithm , 1970 .

[27]  Pierre M. Picard,et al.  Trade, economic geography and the choice of product quality , 2015 .

[28]  A. Hirschman THE PATERNITY OF AN INDEX , 1964 .

[29]  G. Fagiolo Clustering in complex directed networks. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[30]  A. Rose,et al.  One money, one market : the effect of common currencies on trade , 2000 .

[31]  Frank Schweitzer,et al.  Economic Networks: What Do We Know and What Do We Need to Know? , 2009, Adv. Complex Syst..

[32]  Julio Dávila,et al.  Can geography lock a society in stagnation , 2013 .