Bank Financing of Global Supply Chains
May 19, 2025
Summary
Examining the role of banks in the reconfiguration of supply chains after the 2018–19 US-China tariffs, the authors of this working paper show that importers of tariff-hit products were more likely to find new suppliers in other Asian countries if they had a relationship with an Asian-trade finance specialized bank.
View PaperWorking Paper 2025-4
Abstract: Finding new international suppliers is costly, so most importers source inputs from a single country. We examine the role of banks in mitigating trade search costs during the 2018–19 US-China trade tensions. We match data on shipments to US ports with the US credit register to analyze trade and bank credit relationships at the bank-firm level. We show that importers of tariff-hit products from China were more likely to exit relationships with Chinese suppliers and find new suppliers in other Asian countries. To finance their geographic diversification, tariff-hit firms increased credit demand, drawing on bank credit lines and taking out loans at higher rates. Banks offering specialized trade finance services to Asian markets eased both financial and information frictions. Tariff-hit firms with specialized banks borrowed at lower rates and were 15 percentage points more likely and three months faster to establish new supplier relationships than firms with other banks. We estimate the cost of searching for suppliers at $1.9 million (or 5 percent of annual sales revenue) for the average US importer.
JEL classification: G21, F34, F42
Key words: financial frictions, bank lending, supply chains, trade policy
Digital Object Identifier (DOI): https://doi.org/10.29338/wp2025-04
Laura Alfaro is with Harvard Business School, the National Bureau of Economic Research, and the Centre for Economic and Policy Research. Mariya Brussevich is with Ibmec-RJ and the International Monetary Fund. Camelia Minoiu is with the Federal Reserve Bank of Atlanta. Andrea Presbitero is with the International Monetary Fund and the Centre for Economic and Policy Research. The authors are grateful to Viral Acharya, JaeBin Ahn, Salome Baslandze, Daniel Carvalho, Catherine Casanova, Ricardo Correa, Rebecca De Simone, Julian di Giovanni, Simon Fuchs, Ruben Gaetani, Pierre-Olivier Gourinchas, Galina Hale, Peter Haslag, Gazi Kabas, Fernando Leibovici, Rodrigo Leite, Julien Martin, Isabelle Mejean, Tomasz Michalski, Emanuel Moench, Lars Norden, Evren Ors, Tarun Ramodarai, Kim Ruhl, Felipe Saffie, Peter Schott, Toshitaka Sekine, Judit Temesvary, Chenzi Xu, Larry Wall, Jon Willis, and participants at numerous conferences and seminars for helpful comments and discussions. They thank Yuritzy Ramos for outstanding research assistance. This project is supported by the Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, Grant/Award Number SEI-260003/000532/2023. The authors thank the Center for Advancement of Data and Research in Economics (CADRE) at the Federal Reserve Bank of Kansas City for providing essential computational resources that contributed to the results reported in this paper. The views expressed in this paper are those of the authors and do not necessarily represent those of the Federal Reserve Bank of Atlanta; the Federal Reserve System; or the International Monetary Fund, its executive board, or its management.
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