Networks of Foreign Value Added in Exports

Transcription

1 Networks of Foreign Value Added in Exports J. Amador 1 S. Cabral 2 R. Mastrandrea 3 F. Ruzzenenti 4 1 Banco de Portugal & Nova SBE 2 Banco de Portugal 3 IMT School for Advanced Studies 4 University of Groningen 5th Worskhop on GVCs: Updating our Knowledge on GVCs Roma Tre University and Rossi-Doria Centre, March 2018 Disclaimer: The views expressed are those of the authors and do not necessarily reflect those of Banco de Portugal.

2 Outline 1 Motivation 2 Unweighted FVAiX network 3 Weighted FVAiX network 4 Where do we go from here?

3 GVCs and Networks The international fragmentation of production is the new paradigm for world production. Foreign value added in exports (FVAiX) is typically used as a simple indicator of participation in GVCs (Johnson and Noguera, 2013 & Koopman et. al, 2014). GVCs are intrinsically complex because there are multiple relations between value added users and suppliers, thus, network theory offers the right set of tools for analysis. Network graphs highlight relevant features of complex data, notably, the main users and suppliers of value added in GVCs and their interconnections. Aggregate network measures offer insights on issues like density, complexity, hierarchy and resilience.

4 The unweighted network Nodes are the 40 countries in the WIOD database; period Unweighted (binary) network. The criterion for the existence of an edge is defined to reflect the importance of a source country s as a supplier of value added for the production of the exports of country r. A foreign value added threshold is set at 1 percent of total gross exports of the user country. The existence of a clear interpretation for the orientation of the edge, i.e., directed from a country whose value added share in another country s exports is larger than the threshold, makes this network directed.

5 More precisely: a sr = 1 if FVAiX sr 0 otherwise X r > 0.01 for each country s r = 1, 2... N where AM = [a sr ] is the N N connectivity or adjacency matrix. The 1 percent threshold is necessary (though, somewhat arbitrary) to avoid having a complete network. Large countries naturally weight more as suppliers than smaller economies.

6 Motivation Unweighted FVAiX network Goods 2011 Weighted FVAiX network Where do we go from here? Services 2011 Notes: The size of each node is proportional to its total degree and the color of the node is mapped to its indegree, with darker shades indicating higher values. The network graphs are based on the Harel-Koren fast multi-scale algorithm and are drawn with the use of NodeXL.

7 Total Goods Services Centralization of eigenvector centrality Total Goods Services Global clustering coefficient Notes: Network metrics were computed using the R packages statnet and igraph. All aggregate network measures were computed ignoring the directionality of the edges.

8 Main results The goods network is denser than that of services, as classical GVCs relate to the trade of parts and components to be embodied in different stages of manufacturing. Larger countries have bigger nodes and locate in the centre of the network, mostly because they are important suppliers of value added. Some small countries have the darkest nodes (use value added from several sources). From 1995 to 2011, there was an increase in average degree, in line with the expansion of GVCs. The centralisation measures are very high pointing to a concentrated structure dominated by a few central countries. However, it has decreased over time. Global clustering coefficients are high, which suggests the presence of a hierarchical structure and a tendency for countries to group around influential players.

9 The weighted network Since the basic FVAiX network is complete, we examine its backbone structure, keeping for each country only its strongest user and supplier connections. We also study higher-order network properties that can shed light on the complex architecture of GVCs, notably in terms of cyclical triangular relationships. Keep using the same raw material: nodes are the 40 countries in the WIOD database; period

10 Main users 1995 Main users 2011 Notes: The networks are directed and the arrows are oriented from supplier to receiver. The edge width is proportional to the edge weight and those representing flows that are reciprocated are black-shaded. The size of each node is proportional to its share as user of value added in the respective backbone. The network graphs are drawn with the use of NodeXL

11 Main suppliers 1995 Main suppliers 2011 Notes: The networks are directed and the arrows are oriented from supplier to receiver. The edge width is proportional to the edge weight and those representing flows that are reciprocated are black-shaded. The size of each node is proportional to its share as supplier of value added in the respective backbone. The network graphs are drawn with the use of NodeXL

12 DEU USA CHN JPN RUS DEU USA CHN JPN RUS Average Hub centrality (out) Clustering coefficient Notes: Hub centralities of a country reflect its relevance as a supplier in the FVAiX network, while the clustering coefficient (cyclic triangles) measures the interconnectivity among nodes.

13 Main results The fundamental structure of GVCs is organised around regional blocks, with Germany, the US and China acting as hub suppliers in their respective regions. Over time, as GVCs became more global in nature, the networks turned more complex and strongly connected. The change in the structure of the weighted directed network of FVAiX highlights the rising importance of China since 2000, which developed into the largest hub of value-added trade after the US. Results emphasise that 2nd order properties of the network. The increase in Japan s clustering coefficient mirrors the role of Japanese affiliates in East Asian production networks, which typically involve more than two countries, thus increasing the prevalence of cyclical triangles.

14 Research avenues The shape of GVCs keeps changing with an incresing role for services Automation is (will) affecting GVCs Networks are key to study resilience to shocks and the entire set of linkages between countries Networks are necessary to model firms decisions regarding participation in GVCs The role of transaction costs between firms, complex supply-chain management and certification are also topics where GVCs and network analysis interplay.