On March 22, 2018, the Office of the United States Trade Representative (USTR) released a report about China’s practices related to technology transfer. As a result, the USTR proposed an additional duty of 25% on a list of 1,333 products from China. U.S. Customs and Border Protection has started to collect these additional duties for a list of 818 products lines imported from China, which include metals, transportation products, electronics, plastics, and chemicals.
Production Costs Already Increasing
China is the number one exporter of goods to the United States. These tariffs have the potential to perturb trade patterns and change the economic landscape as their effect ripples through the supply network of manufactured products. As the supply network adjusts, a new global trade equilibrium will emerge. During this metamorphosis, (re)insurers may need to re-evaluate their contingent business interruption (CBI) risk management strategies and assess the impact of tariffs on their CBI book of business.
For products that have had initial tariffs imposed, it is estimated that these tariffs will affect imports from China worth USD 34 billion. These additional duties are already raising production costs for American automobile manufacturers because they use imported parts to build cars in the U.S.; for example, the Hyundai Motor Company imports car parts into its Alabama plant. General Motors has cut its profit outlook for this year, citing higher costs for steel and aluminum, amid other reasons. Other automakers, such as Fiat Chrysler and Ford, have also reported lower profits, and vehicle prices could increase by several thousand dollars.
Estimating the Impact
Currently, there is a latency period between the onset of the trade war and observing its potential impact across multiple industries (e.g., automotive, consumer electronics, etc.). In the meantime, faced with possible but unanticipated risks, (re)insurers can proactively stress-test their portfolios by running several “what-if” scenario analyses and using the resulting analytics to selectively equip themselves to navigate the changing risk terrain.
Using the AIR Supply Chain Risk Model, we performed a “what-if” scenario analysis to estimate the potential impact to businesses in the U.S. resulting from 20% higher tariff costs from China. The risk model can be used to analyze supply chain networks and estimate the product value at risk (PVaR), a proxy for the possible loss in production of a product.
Results from this analysis show that, for the U.S., final and intermediate products for automobiles and electronic computers could potentially suffer PVaR ranging from 16% to 20%. This implies that the manufacture of automobiles and computers in the U.S. is dependent on the flow of specific tariffed goods from China. When these imports decrease, unless U.S. manufacturers take mitigating measures, a loss in domestic production could be the immediate reaction.
An insurer may observe an increase of uncertainty for U.S. manufacturers, as they could shift suppliers away from China to other parts of the world with unique regional vulnerabilities. Due to the interconnected nature of the supply chain, the consequence of the trade war between the U.S. and China manifests globally. Results from AIR’s analysis indicate that both NAFTA countries, Canada and Mexico, expect to experience PVaR in the range of 15% for automobiles and computers, which suggests insurers could perceive an upsurge in risk across these two countries.
Re-evaluate and Rebuild
In the coming months, companies will be forced to re-evaluate their supply networks to rebuild them robustly. For companies with insurance policies for trade disruption, perhaps the fine print may include coverage for disruption or restriction by government actions. For insurers, concentration of risk is clearly interwoven across multiple industries and many countries. This trade war could result in the development of supply chain risk intrinsically different from today’s, with changes to exposure concentration and unexpected risk aggregation.