TY - UNPB
T1 - Global Sourcing under Tariffs: Time Series Analysis of Product-Level Evidence
AU - Zhang, James
AU - Dabadghao, Shaunak S.
AU - Udenio, Maximiliano
PY - 2023
Y1 - 2023
N2 - Global sourcing is a complex process to acquire products and services from international sources, and therefore is subject to various disruptions. This paper focuses on the potential disruptions arising from the large-scale tariffs during 2018-2019. Drawing on tariff implications from analytic models of global supply network design, we specifically examine the patterns of global sourcing and how tariffs could disrupt global supply chains by investigating time series of monthly sourced amounts. We draw 222 manufacturing firms from FactSet Shipping database, with 3,348,595 unique observations covering time period between January 2014 and December 2019. By aggregating sourcing amounts on each firm, and applying multivariate time series clustering algorithm, we identify seven unique clusters for these firms. We further examine the disruptive effects of these tariffs by using intervention analysis of time series for each cluster. We find that firms in each cluster increase their sourcing amounts before or during tariff time periods. Our results further show that while some firms have a significant disruptive effect, other firms still maintain pre-tariff sourcing behaviors. An additional analysis reveals that firm size, growth potential, and firm profitability are associated with firms’ ability to deal with disruptions. Overall, our results have important implications for global supply chain management.
AB - Global sourcing is a complex process to acquire products and services from international sources, and therefore is subject to various disruptions. This paper focuses on the potential disruptions arising from the large-scale tariffs during 2018-2019. Drawing on tariff implications from analytic models of global supply network design, we specifically examine the patterns of global sourcing and how tariffs could disrupt global supply chains by investigating time series of monthly sourced amounts. We draw 222 manufacturing firms from FactSet Shipping database, with 3,348,595 unique observations covering time period between January 2014 and December 2019. By aggregating sourcing amounts on each firm, and applying multivariate time series clustering algorithm, we identify seven unique clusters for these firms. We further examine the disruptive effects of these tariffs by using intervention analysis of time series for each cluster. We find that firms in each cluster increase their sourcing amounts before or during tariff time periods. Our results further show that while some firms have a significant disruptive effect, other firms still maintain pre-tariff sourcing behaviors. An additional analysis reveals that firm size, growth potential, and firm profitability are associated with firms’ ability to deal with disruptions. Overall, our results have important implications for global supply chain management.
U2 - 10.2139/ssrn.4546817
DO - 10.2139/ssrn.4546817
M3 - Working paper
SP - 1
EP - 48
BT - Global Sourcing under Tariffs: Time Series Analysis of Product-Level Evidence
PB - Social Science Research Network (SSRN)
ER -