One argument for tariffs relies on the idea that they will expand U.S. manufacturing employment. In theory, a unilateral tariff would advantage U.S. manufacturing firms relative to foreign competition and result in more U.S. job opportunities. However, experience with previous unilateral increases in tariffs casts doubt that they will increase U.S. employment for two reasons: U.S. tariffs result in higher input costs for U.S. firms and sovereign nations retaliate against U.S. exports.
Research studying the U.S.-China trade war in 2018 and 2019 found that that these costs of tariffs outweighed any benefits and resulted in modest job losses. Extrapolating this evidence to today suggests that current tariff scenarios now in play—on China alone—could cost between 955,000 and 3.4 million U.S. jobs (Figure 1a) and add 0.6 to 2.0 percentage points to the U.S. unemployment rate (Figure 1b). We explain these calculations below.
Potential labor market costs from three U.S.-China tariff scenarios
Sources: Authors’ calculations based on Flaaen and Pierce, “Disentangling the Effects of the 2018-2019 Tariffs on a Globally Connected U.S. Manufacturing Sector,” 2024, and Michael Waugh, “The Consumption Response to Trade Shocks: Evidence from the US-China Trade War,” 2019. Underlying employment data from U.S. Bureau of Labor Statistics (June 2025).
The role of rising input costs
An important feature of modern international trade is that most trade is in inputs, not final products. The classic caricature of international trade in textbooks of trading cloth for wine could not be further from the truth. Modern-day trade is about intermediate products that cross borders multiple times, with value added at each point in the production chain.
To put this in perspective, more than 56 percent of all U.S. imports in 2024 were intermediate goods (Figure 2).
These industrial inputs and capital goods complement U.S. employment in the production of manufactured goods. A higher tariff on these intermediate goods increases the production costs of U.S. manufacturing firms, depressing employment.
Economists at the Federal Reserve Board studied this force during the U.S.-China trade war in 2018 and 2019. They estimated that the increase in tariffs on China at that time led to the loss of 230,000 American manufacturing jobs through rising cost of these inputs (“Disentangling the Effects of the 2018-2019 Tariffs on a Globally Connected U.S. Manufacturing Sector” by Flaaen and Pierce). Moreover, they found no direct benefit of tariffs for industries that were more protected.
Using the estimates from Flaaen and Pierce, we can calculate the employment effects, through the input costs channel, of relevant tariff scenarios. As of this writing, the effective U.S. tariff rate on China is 28.2 percentage points higher than before the current trade war began on February 1. This rate is temporarily in place of the 125 percent tariffs (an approximately 100 percentage point increase) that the U.S. imposed on April 9 and then suspended for 90 days in a May 12 agreement between the U.S. and China.
The dark blue bars in Figure 1a scale up the effects of rising input costs for these tariff scenarios, as well as a hypothetical trade deal that splits the difference. The current prevailing tariff rate would cost almost 650,000 U.S. jobs. Snapping back to the unprecedentedly high tariffs imposed this spring would cost 2.3 million jobs.1
In Figure 1b we translated these lost jobs into increases in the U.S. unemployment rate, stacked atop the 4.1 percent unemployment rate as of the end of the second quarter of 2025. Across these scenarios, rising input costs alone (again the dark blue segments) would add between 0.4 and 1.4 percentage points to the unemployment rate.
The role of retaliation
A second essential observation about tariffs is that sovereign nations have control over their own trade policies and often retaliate. This retaliation can be harmful because it reduces U.S. sales abroad, and thus the scale of operations and employment at home. This harm accrues to the U.S. on aggregate but can also be especially concentrated geographically.
The lessons from the U.S.-China trade war in 2018 and 2019 are informative about this channel as well. Ongoing research by Michael Waugh constructs county-level exposure metrics to Chinese retaliation during the first U.S.-China trade war.2 A key finding is that counties more exposed to Chinese retaliation experienced employment declines. Across the U.S., this research estimated 87,000 jobs were lost during 2018 and 2019 due to Chinese retaliation.
Extrapolating to the current time period, the teal bars in Figure 1 report the estimated job losses and unemployment rate increase associated with tit-for-tat Chinese retaliation under these three tariff scenarios. Retaliation under the current scenario costs another 307,000 jobs (in addition to input cost effects) and adds 0.2 percentage points to the unemployment rate. Retaliation after a 100 percentage point tariff increase would cost an estimated 1.1 million jobs and add 0.6 percentage points to the unemployment rate.
Retaliation is local
Vulnerability to Chinese retaliation varies greatly across the U.S. and even within U.S. states, depending on their shares of jobs in China-exporting industries. Figure 3 shows the county-by-county vulnerability at the height of Chinese tariff retaliation in 2019.
Soybean farming is a good example of the higher vulnerability of certain places to Chinese retaliation. When China retaliated in 2018, U.S. soybean exports to China declined dramatically (Figure 4).
This fall in exports represents a loss of market access for farmers growing these crops. Because soybean farming is concentrated in the Midwest, counties in this region were more exposed to Chinese retaliation and consequently suffered job losses.
Although these calculations date to the end of the last trade war, we expect geographic vulnerability would look broadly similar to the Figure 3 map today, with swathes of the Midwest and West more exposed to Chinese retaliation.
Do tariffs save some jobs?
Perhaps tariffs could generate significant, off-setting job gains. Protection could theoretically bolster specific domestic industries or companies, depending on available substitute inputs, ability to “reshore” production to the U.S., and changes in technology.
The evidence is not encouraging from the primary examples of targeted U.S. tariff protections in recent years. In June 2018, the U.S. imposed tariffs on all imports of steel (25 percent) and aluminum (10 percent). Seven years later, these appear to have done little to reverse the 35-year decline in steel and aluminum production jobs in the U.S. (Figure 5).
The same observation applies to a short-lived application of steel tariffs in 2002, which were withdrawn a year later with sector employment lower than when they were put in place. U.S. production of steel and aluminum today is roughly the same as 1990, suggesting technology and increased productivity play a significant role in the decline of these metals jobs, regardless of foreign competition or protection.
The broader evidence from the U.S.-China trade war is not encouraging either. Flaaen and Pierce looked for evidence of job gains in manufacturing from protections put in place during the 2018–2019 trade war. They found tariff protection was generally associated with a net reduction in jobs, as the negative impact of input costs and retaliation “more than offsets a small positive effect from import protection.”
In addition to this sectoral view, one could look for geographic evidence of job gains from protection. Waugh looked for employment gains in counties that experience more tariff protection. Like Flaaen and Pierce, he found small, negative employment effects for more-protected counties relative to less-protected counties. In other words, there is little evidence that protection leads to better employment outcomes.
Hovering over all: Uncertainty
Beyond the cost of manufacturing inputs and retaliation, heightened economic uncertainty around trade can also contribute to job loss. An index of trade policy uncertainty established with co-authors by Minneapolis Fed Research Director Andrea Raffo is currently more than four times its previous peak during the 2018–2019 trade war, and more than 10 times its typical level in recent decades.
Such uncertainty can motivate firms to alter or postpone investment decisions and households to trim spending and save for a possible downturn. “Even if higher tariffs never materialize, you can still have both of these significant impacts on the economy,” Raffo said in a recent interview, resulting in lower growth than otherwise.
This article has not touched on the separate consequences of tariffs for American households as consumers; the Minneapolis Fed continues to explore these costs in separate research. Economists working to gauge the impact of today’s U.S. trade policy are aiming at a moving target. Nonetheless, available evidence from past episodes strongly suggests that workers are unlikely to come out winners from a trade war.
Endnotes
1 These calculations are linear, multiplying the job costs attributable to the percentage point increase in U.S. tariffs on China in 2018 to match the scale of these current tariff-increase scenarios. At high tariff levels the estimates might be considered conservative, as they do not account for nonlinear effects, such as from financial market turmoil or compromised global value chains.
2 See Michael Waugh, “The Consumption Response to Trade Shocks: Evidence from the US-China Trade War,” 2019. This research in ongoing and will be updated in a forthcoming staff report from the Minneapolis Fed.
Jeff Horwich is the senior economics writer for the Minneapolis Fed. He has been an economic journalist with public radio, commissioned examiner for the Consumer Financial Protection Bureau, and director of policy and communications for the Minneapolis Public Housing Authority. He received his master’s degree in applied economics from the University of Minnesota.