International Automotive Production Networks: How the Spider Web is Pulled Together

Blázquez–Gómez, Leticia

González-Díaz, Belén

University of Castilla-La Mancha - SPAIN

XIII Annual ConferenceEUROPEAN TRADE STUDY GROUP

Copenhagen, September 8-10 2011

International Automotive Production Networks: How the Spider Web is Pulled TogetherMotivation and Aims

Motivation• Growing integration of countries: formidable increase of international

trade. International division of labour ( due to IPN):

1) Spectacular rise of intermediate commodities flows.2) Global diversification of trade.3) Complex networks of direct and indirect relations between individuals, firms,

nations, institutions.• Traditional economic and trade theories are too stylized. Better theoretical

and methodological tools are necessary. Social network analysis: empirical and helpful method to address the evolvement of

the structural configuration of the global production networks.Aims• Analysis of transformations in the auto international production network in

the last decade: Structural evolvement of the IPN: nature, patterns and significance of linkages,

position and importance of the nations in the structure, new characters. Which role are the emerging countries playing in the evolvement of the IPN? How

significant can their role become?. Does a regional configuration of the network remain? Are the architectures and

dynamics of the regional blocks similar? Which has been the impact of RTAs on this regional configuration?.

How do IPNs combine geographic dispersion of the value chain with spatial integration of participants? Does this combination depend on the factorial intensity of components?.

International Automotive Production Networks: How the Spider Web is Pulled TogetherThe Dataset

Our bilateral trade flows dataset Based on UN COMTRADE

• Bilateral imports of the Automotive industry (Final Goods and its Parts and Components) disaggregated at six-digit level of Combined Nomenclature (HS 1992) for the years 1996 and 2009;

• Observations for 174 countries• Following Turkcan (2009) & Kaminski and Ng (2001) we provide a more

extensive and complete code list for automotive Final Goods and their corresponding P&C.

• Following the typology of Peneder (1999) we have distingued 4 groups of commodities according to their factorial intensity:

Capital Intensive parts and components Labour Intensive id. Technology Driven id. Mainstream Driven id.

International Automotive Production Networks: How the Spider Web is Pulled TogetherThe trade in the Automotive Industry

What’s going on in the automotive industry trade?

Automotive P&C world export shares (%) Automotive P&C world import shares (%)

Automotive Final Goods world export shares (%)

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Transfer of activity from the more advanced countries to the emerging economies

Source: author’s calculation, based on UN COMTRADE (using the software Pajek)

International Automotive Production Networks: How the Spider Web is Pulled TogetherSocial Network Analysis

• Social Network Analysis: Emphasis on the relationship between trade partners and the structure

of the system. Dealing with some of the shortcomings of aggregated data. Complement other empirical analysis: Gravity models, global value

chain models… Economic interpretation of results in the light of international trade

theory. Indicators used

• Density (, cohesiveness of the network): number of arcs, L, divided by the maximum possible number of arcs (pair of vertices)

• Degree (d): number of vertices adjacent to it or, equivalently, the number of lines incident with it. Indegree and Outdegree: number of arcs received and send by a vertex. Important as centrality measure (an actor with a large degree is in direct contact to many other actors occupying a central location. In contrast, actors with low degree are clearly peripheral in the network).

• Degree centralization of a network is the variation in the degrees of vertices divided by the maximum degree variation which is possible in a network of the same size. It expresses the extent to which a network has a centre. More variation in the centrality scores of vertices yields a more centralized network.

• Closeness centrality of a vertex is the number of other vertices divided by the sum of all distances between the vertex and all others. Therefore, the larger distances yield lower closeness centrality.

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International Automotive Production Networks: How the Spider Web is Pulled TogetherSocial Network Analysis

Indicators used • Betweeness rests on the idea that an actor is more central if it is more important as an

intermediary in the network:

• Betweenes centrality: an actor is central if it lies between other actors on their geodesics, implying that to have a large “betweeness” centrality

• Betweenness centralization is the variation in the betweenness centrality of vertices divided by the maximum variation in betweenness centrality scores possible in a network of the same size

• Prestige of a vertex : number of arcs it receives; is the standarized indegree of a vertex. Proximity prestige index of a vertex considers all vertices within the influence domain of a vertex but it attaches more importance to a nomination if it is expressed by a closer neighbour. Maximum prestige is achieved if a vertex is directly chosen by all other vertices.

• A k-core is a maximal subnetwork in which each vertex has at least degree k within the subnetwork, that is, each node is adjacent to at least a minimum number, k, of the other nodes in the subgraph. A k-core identifies relatively dense subnetworks, so they help us to find cohesive subgroups.

International Automotive Production Networks: How the Spider Web is Pulled TogetherStructural Properties of the Automotive International Trade Network

  P&C Final Goods

  1996 2009 1996 2009

Arcs (#) 1133 1262 1029 1125

Density 0.038 0.042 0.035 0.037

Average Degree (Number of partners) 12.530 13.820 11.470 12.430

In- Degree/Outdegree (Average) 6.549 7.253 5.948 6.467

Network Centralization (symmetrized network) 0.691 0.861 0.838 0.781

In-Degree Centralization 0.032 0.028 0.030 0.038

Out-Degree Centralization 0.722 0.894 0.866 0.811

Input Closeness Centrality 0.087 0.084 0.060 0.072

Output Closeness Centrality 0.093 0.092 0.062 0.078

Closeness Centrality 0.487 0.509 0.503 0.510

Betweeness Centrality 0.001 0.001 0.001 0.001

Betweness Centralization 0.059 0.040 0.017 0.034

Pearson Correlation: All Closeness & Betweeness Centrality 0.473 0.567 0.564 0.758

Pearson Correlation: Input & Output Closeness Centrality -0.021 -0.118 -0.171 -0.253

Source: author’s calculation, based on UN COMTRADE (using the software Pajek)

International Automotive Production Networks: How the Spider Web is Pulled TogetherStructural Properties of the Automotive International Trade Network

Automotive P&C network, 2009 (*)

Automotive P&C IN-degree network,2009

(*) The size of vertices is related to their all-degreeSource: author’s calculation, based on UN COMTRADE (using the software Pajek)

Automotive P&C OUT-degree network,2009

Automotive Final Goods network, 2009 (*)

A large proportion of countries do not have any P&C export relation with the rest of countries

The indegree index vary in a very narrow range.The import P&C network has not a clear centre.

International Automotive Production Networks: How the Spider Web is Pulled TogetherStructural Properties of the Automotive International Trade Network

 P&C Final Goods

  1996 2009 1996 2009

Arcs (#) 1133 1262 1029 1125

Density 0.038 0.042 0.035 0.037

Average Degree (Number of partners) 12.530 13.820 11.470 12.430

In- Degree/Outdegree (Average) 6.549 7.253 5.948 6.467

Network Centralization (symmetrized network) 0.691 0.861 0.838 0.781

In-Degree Centralization 0.032 0.028 0.030 0.038

Out-Degree Centralization 0.722 0.894 0.866 0.811

Input Closeness Centrality 0.087 0.084 0.060 0.072

Output Closeness Centrality 0.093 0.092 0.062 0.078

Closeness Centrality 0.487 0.509 0.503 0.510

Betweeness Centrality 0.001 0.001 0.001 0.001

Betweness Centralization 0.059 0.040 0.017 0.034

Pearson Correlation: All Closeness & Betweeness Centrality 0.473 0.567 0.564 0.758

Pearson Correlation: Input & Output Closeness Centrality -0.021 -0.118 -0.171 -0.253

Source: author’s calculation, based on UN COMTRADE (using the software Pajek)

International Automotive Production Networks: How the Spider Web is Pulled TogetherThe Role of Countries in the Automotive International Production Network

Source: author’s calculation, based on UN COMTRADE (using the software Pajek)

Indegree Import Share Outdegree Export Share Outdegree Export Share Indegree Import Share Outdegree Export Share Outdegree Export Share

China 6 1,01% 23 0,80% 6 0,02% 4 3,52% 161 13,77% 62 0,65%Germany 11 6,87% 123 15,18% 129 20,00% 12 7,78% 115 13,33% 128 21,95%Japan 9 1,83% 130 14,17% 154 16,67% 7 2,06% 113 8,12% 146 15,17%USA 4 14,98% 114 17,14% 95 7,23% 6 14,07% 100 7,65% 100 6,83%Mexico 3 3,67% 5 4,50% 20 4,23% 6 3,59% 18 4,74% 16 4,53%Korea 4 1,30% 71 0,79% 88 1,29% 4 1,03% 80 4,66% 90 3,86%France 8 4,17% 89 6,78% 85 6,97% 10 3,87% 72 4,49% 64 5,26%Italy 7 2,38% 90 4,01% 57 3,01% 9 2,05% 62 2,99% 39 2,15%Hungary 8 0,20% 4 0,45% 1 0,02% 9 1,11% 33 2,26% 4 0,07%Canada 3 8,93% 8 4,52% 8 11,11% 4 4,14% 6 2,23% 6 4,68%Poland 7 0,71% 4 0,02% 0 0,00% 6 1,34% 22 2,11% 6 0,68%Czech Rep. 6 0,45% 7 0,42% 13 0,12% 8 1,39% 14 1,93% 22 1,44%Spain 6 4,07% 26 2,54% 38 5,28% 9 3,08% 22 1,90% 34 5,20%UK 7 5,32% 94 3,77% 78 5,01% 12 3,59% 45 1,90% 62 3,43%Austria 5 1,43% 13 1,35% 4 0,30% 6 1,13% 9 1,03% 6 0,40%B&L 8 3,55% 22 1,52% 37 5,53% 11 2,40% 34 1,00% 40 3,18%Brazil 9 1,31% 18 0,52% 11 0,35% 9 1,06% 21 0,82% 19 0,78%Netherlands 8 2,06% 27 0,44% 32 1,00% 9 1,33% 23 0,76% 27 0,30%Thailand 2 1,47% 7 0,22% 3 0,00% 7 0,99% 18 0,74% 60 1,36%Slovakia 7 0,10% 3 0,08% 1 0,01% 7 0,80% 3 0,64% 5 0,39%Sweden 11 1,86% 43 2,48% 25 0,69% 9 0,93% 15 0,64% 15 0,33%Romania 4 0,11% 0 0,00% 2 0,01% 9 0,55% 11 0,57% 1 0,02%India 7 0,29% 19 0,06% 15 0,04% 6 0,99% 48 0,39% 16 0,13%Finland 7 0,40% 18 0,35% 4 0,05% 7 0,44% 19 0,24% 1 0,00%Indonesia 5 0,79% 6 0,01% 0 0,00% 7 0,74% 9 0,23% 4 0,04%Portugal 6 0,92% 5 0,32% 6 0,45% 7 0,51% 6 0,20% 3 0,03%Russia 9 0,32% 19 0,21% 21 0,12% 10 1,28% 15 0,20% 16 0,13%Argentina 6 0,66% 4 0,24% 2 0,33% 7 0,67% 4 0,16% 6 0,75%Singapore 10 1,15% 15 0,28% 4 0,04% 6 0,90% 13 0,16% 5 0,01%Philippines 8 0,30% 1 0,13% 0 0,00% 9 0,10% 2 0,15% 1 0,01%Turkey 7 0,66% 11 0,02% 8 0,05% 12 1,30% 17 0,14% 22 1,23%Malaysia 7 0,44% 4 0,22% 2 0,00% 8 0,47% 3 0,11% 1 0,00%Australia 6 1,07% 7 0,11% 6 0,16% 6 0,90% 7 0,03% 6 0,20%Lithuania 10 0,04% 2 0,01% 3 0,01% 10 0,05% 1 0,00% 2 0,01%

1996 2009Parts & Components Final Goods Parts & Components Final Goods

Has changed the role of countries in the automotive production network?

International Automotive Production Networks: How the Spider Web is Pulled TogetherRegional configuration of the Automotive International Production Network and the

impact of RTAs

• Does the continental effect matter in the Automotive network? – Positive continental effect in the number of trading linkages between countries,

except for Oceania• More striking for Europe.

• Are the architectures and dynamics of the regional blocks similar?– North America is a region defined by USA economic and political weight.– The structure of the automotive Asian networks have become much more centred

(export flows tend to be increasingly concentred around a few Asian countries). • Increasing trading links especially in Thecnology driven P&C.

– In Europe, the network has extended and become less centralized. • The enlargement of the EU to the East has been crucial to the maintenance of a

competitive European network. • Increasing trading links especially in Capital and Labour intensive P&C.

• Which has been the impact of RTAs on this regional configuration?– Positive effect in the NAFTA, EU and ASEAN.

International Automotive Production Networks: How the Spider Web is Pulled TogetherAutomotive P&C Subnetworks. Factorial Intensity Approach

Source: author’s calculation, based on UN COMTRADE (using the software Pajek)

Top-countries highly connected: Germany, Japan, France, Italy, Spain, U.K. and USA…

although new players are reaching relevant positions in this market.

International Automotive Production Networks: How the Spider Web is Pulled TogetherConcluding Remarks

• The global automotive network is:• increasingly tight, especially in P&C; • increasingly star-structured and centralized (export): benefit from the scale economies not

only in the production but also in the supply-base.• Still concentrated in a small although increasing number of countries.

• China has become in a central country of the network, joining the traditional Triad (Germany, USA and Japan).

• Escalating role of CEECs countries• Strong and stable regional architectures prevails in the industry.

• The three main regions (Europe, USA and Asia) shows different architectures and dynamics in the conformation of the networks.

• The RTAs have boosted the creation of regional clusters.• The inclusion of emerging countries in the IPN and their fast technological upgrading have

increased the heterogeneity of the networks and made easier the exploitation of comparative advantages.

• Important limitation: P&C suppliers follow the automakers companies.• Main restructuration in Technology driven and Labour intensive P&C.

• We observe a dispersion of resources and capabilities across national boundaries and a paralel integration of a growing, but still limited, number of dispersed, specialized clusters.

International Automotive Production Networks: How the Spider Web is Pulled Together

Blázquez–Gómez, Leticia

González-Díaz, Belén

University of Castilla-La Mancha - SPAIN

XIII Annual ConferenceEUROPEAN TRADE STUDY GROUP

Copenhagen, September 8-10 2011