Abstract

As the world economy has become increasingly integrated the spectre of transnational supply chains has become a central feature of globalisation. The smooth and unfettered working of transnational supply chains has facilitated efficiency increasing changes to business operations (such as just in time inventory management). The automotive sector worldwide has been at the forefront of internationally integrated supply systems. The European Union (EU) has, in part, been structured to reduce friction in Europe-wide supply chains through the single market. Transnational supply chains are at the heart of United Kingdom (UK) – EU trade, and the UK’s departure from the EU’s single market (Brexit) will increase friction in international trade. This case study of the UK’s automotive sector uses a social network approach to analyse supply chain linkages between the UK, EU and other trading partners, and how these could be impacted as a result of Brexit. We use data from Trade in Value Added (TiVA) and World Input-Output Database (WIOD) to map supply chains, estimate total value-added in exports and examine how Brexit is likely to impact the competitiveness of UK exports. Results confirm that the UK’s automotive sector is closely integrated with the EU. To offset the loss of UK’s export competitiveness after Brexit, trade facilitation measures complemented with a duty drawback scheme could be an option in the short run. Policy measures are, however, unlikely to replace the benefits of duty-free and frictionless access enjoyed under single market trading arrangements. This suggests that the UK automotive sector, which is primarily comprised of globally active firms, may have to reconfigure supply chain arrangements and in the long run alter how decisions pertaining to locations are made. Keywords: Brexit, global value chains, input-output linkages, WIOD.

Highlights

  • Global value chains (GVCs) involve production where the output of a firm in one country is used by another firm in second country to produce a more complex product which, in turn, may be used by another firm for further processing before being consumed as the final product (World Bank et al 2019)

  • We derive a set of network indicators such as revealed comparative advantage (RCA), economic weight, connections between countries as measured by indegree and outdegree, eigenvector centrality and PageRank ‒ a probabilistic score based on a hierarchy of nodes by link popularity and where a node is ranked higher if there are more links pointing to it

  • The departure of the United Kingdom (UK) from the single market and customs union could result in the automobile industry facing most favoured nation (MFN) tariffs under WTO commitments at 10% on cars and 2 - 4% on components

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Summary

Introduction

Global value chains (GVCs) involve production where the output of a firm in one country is used by another firm in second country to produce a more complex product which, in turn, may be used by another firm for further processing before being consumed as the final product (World Bank et al 2019). Our paper uses the Organisation of Economic and Cooperation Development (OECD)-WTO Trade in Value-Added (TiVA) database and World Input-Output Data (WIOD) on Inter-Country InputOutput (ICIO) tables for 2000–14 to provide an insight into the expected impact on the automotive sector. Another contribution of this paper is a detailed insight into the implications for future UK trade policy, which is relevant in light of the COVID-19 pandemic and the UK’s departure from the EU at the end of 2020. The paper is structured as follows: section two provides an overview of the supply chain linkage literature and the linkages of UK supply chains; section three draws attention to how the UK’s automobile sector is likely to be impacted by Brexit; section four examines the impact of Brexit on UK’s export competitiveness; section five concludes

Characterising supply chains
Data and methodology
UK’ s trade-based supply chains
Case study
Estimates on UK Losses when Exports lose Competitiveness
Findings
Conclusion

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