Abstract

In 2018, after 25 years of the North America Trade Agreement (NAFTA), the United States requested new rules which, among other requirements, increased the regional con-tent in the production of automotive components and parts traded between the three part-ner countries, United States, Canada and Mexico. Signed by all three countries, the new trade agreement, USMCA, is to go into force in 2022. Nonetheless, after the 2020 Presi-dential election, the new treaty's future is under discussion, and its impact on the automo-tive industry is not entirely defined. Another significant shift in this industry – the acceler-ated rise of electric vehicles – also occurred in 2020: while the COVID-19 pandemic largely halted most plants in the automotive value chain all over the world, at the reopen-ing, the tide is now running against internal combustion engine vehicles, at least in the an-nouncements and in some large investments planned in Europe, Asia and the US. The definition of the pre-pandemic situation is a very helpful starting point for the analysis of the possible repercussions of the technological and geo-political transition, which has been accelerated by the epidemic, on geographical clusters and sectorial special-isations of the main regions and countries. This paper analyses the trade networks emerg-ing in the past 25 years in a new analytical framework. In the economic literature on inter-national trade, the study of the automotive global value chains has been addressed by us-ing network analysis, focusing on the centrality of geographical regions and countries while largely overlooking the contribution of countries' bilateral trading in components and parts as structuring forces of the subnetwork of countries and their specific position in the overall trade network. The paper focuses on such subnetworks as meso-level structures emerging in trade network over the last 25 years. Using the Infomap multilayer clustering algorithm, we are able to identify clusters of countries and their specific trades in the automotive internation-al trade network and to highlight the relative importance of each cluster, the interconnec-tions between them, and the contribution of countries and of components and parts in the clusters. We draw the data from the UN Comtrade database of directed export and import flows of 30 automotive components and parts among 42 countries (accounting for 98% of world trade flows of those items). The paper highlights the changes that occurred over 25 years in the geography of the trade relations, with particular with regard to denser and more hierarchical network gener-ated by Germany’s trade relations within EU countries and by the US preferential trade agreements with Canada and Mexico, and the upsurge of China. With a similar overall va-riety of traded components and parts within the main clusters (dominated respectively by Germany, US and Japan-China), the Infomap multilayer analysis singles out which com-ponents and parts determined the relative positions of countries in the various clusters and the changes over time in the relative positions of countries and their specialisations in mul-tilateral trades. Connections between clusters increase over time, while the relative im-portance of the main clusters and of some individual countries change significantly. The focus on US and Mexico and on Germany and Central Eastern European countries (Czech Republic, Hungary, Poland, Slovakia) will drive the comparative analysis.

Highlights

  • In this paper we focus on the changing composition of international trade in automotive components and parts, analyzed on the basis of bilateral trade flows

  • With our analysis we aim to identify the meso-level entities that have characterized the international trade in automotive components and parts over the period 1993-2018

  • How can we identify the clusters of countries that define the trade network without reference to conventional geographical areas but rather to the recurring pattern of interactions in their bilateral trade flows in various components? Having identified these clusters, what is the contribution of countries and of automotive components in determining the relative importance and structure of the various clusters? Thirdly, what changes occur in the structure of those clusters over time, i.e., in the relative positions of countries and their specializations in multilateral trades?

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Summary

Introduction

The automotive industry is having an increasing impact on the world economy's growth (Helper & Sako, 2010). Environmental constraints embedded in EU and China policies (DRC, 2019; European Commission, 2019) led to changes in products (cars and their components and parts) and their production technologies, and in patterns of mobility, technologies and infrastructures These structural changes make it necessary to extend analysis beyond the car sector to encompass the entire automotive and mobility sectors, drawing on several sources of information: OEMs' strategies and the changing locations of their suppliers in the global value chains; technological changes in products (cars, automotive components and parts) and in production technologies and materials; industrial and environmental policies; current individual and collective mobility infrastructures, and plans for their development; dynamics of consumers preferences and needs concerning individual mobility and the type of vehicles satisfying their needs, ranging from new to used vehicles, from individual vs shared vehicles, from compact cars to sport utility vehicles (SUV); changes in preferential trade agreements and their impact on trade networks of automotive components and parts. 11 Selected Figures and Tables marked with the symbol can be browsed on Tableau Public on line with respect to data and community detection (part A), and to flows within and between clusters (part B)

Issues in the network analysis of automotive trade of components and parts
Data description
A multilayer method for module detection
Infomap multilayer algorithm
The multilayer model of international trades over time
Results: clusters of automotive trade and their determinant over time
Meso-scale entities, by year
Infomap flow by country and layer of export and import SITC codes
From Infomap flow to trade shares: patterns of trades by cluster
Findings
Patterns of trades of the three main clusters
Full Text
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