In March 2025, China let the export licenses of hundreds of American beef plants quietly expire. Within months, US beef exports to China had dropped more than 90 percent, and Australian ranchers picked up the slack. Soybean farmers have lived some version of this before. So may the shop owners in an import-dependent commercial district, watching supplier prices creep up over a trade fight they had no part in.
Everyone reads these as national stories. Much harder is answering three questions: Where do these shocks become economically visible? When do local economies begin adjusting? And why do some places bear the costs while others barely notice?
That is the question this research programme is built to answer. Existing measures usually observe geopolitical risk from above: News-based indices identify when geopolitical tension rises; firm-level measures identify which companies discuss political risk; and fragmentation models estimate which countries or sectors would bear the largest losses. None, by itself, tells us where a particular bilateral relationship is embedded within the local economy.
This instalment begins there. Geopolitical fragmentation may be discussed nationally, but it is experienced through particular industries and local economies. Before we can understand timing or mechanisms, we first need to know where different international relationships are economically embedded.
Two dimensions of exposure
Exposure is often discussed as though it were a characteristic of countries. To understand how geopolitical fragmentation reaches workers and local labour markets, exposure must also be measured geographically.
We also need to discuss what it even means for a place to be exposed. Exposure has at least two different dimensions. One is whether a place is unusually dependent on a trading relationship - Specialization. The other is whether that place contributes a large share of the nation’s total trade with that partner - Contribution.
The geography of geopolitical exposure
Exposure has four different meanings
Two lenses, applied to two trade flows. Specialization asks how dependent a county is on a given trade relationship; contribution asks how much that county matters to the national total.
More on the two exposures: the specialization measure follows a familiar idea from economic geography. Regional economists use location quotients to identify places where an industry occupies an unusually large share of local employment relative to the national average. Contribution follows a different logic: closer to the “granular” view of aggregate economic activity, where a small number of large units can move a national total simply by virtue of their size. The same pattern shows up starkly at the state level: Texas alone generates over a fifth of all US exports, and just six states account for more than half, while the counties most dependent on trade tend to be small, rural, and nowhere near that list.
Here, that logic is extended from industries to international relationships: a county is highly specialized when its employment is unusually concentrated in industries tied to a particular partner.
Also, the two exposure figures also don’t move together: counties that sell heavily to China are almost never the same counties that compete with Chinese imports. Across America, the correlation is effectively zero: export exposure and import-competition exposure correlate at 0.03.
There is no one geography of China exposure
The maps reveal something that sounds counterintuitive: there is no single geography of China exposure.
Irion County, Texas has about 1,600 people. In our exposure map, it sits near the top for China export exposure. Brookings flagged the same county independently in 2025, using the tariff list as one of a handful of small counties most exposed to China’s 2025 retaliatory tariffs.
In both studies, population is a bad predictor here. Across the data, county size explains under 1 percent of the variation in export exposure. It explains about 12 percent of a related but different measure: how much a county contributes to the national trade total, where big just tends to mean big. Hence, specialization captures dependence. Small places can nevertheless be highly exposed when a large share of local employment is concentrated in internationally connected industries.
The idea that trade shocks have a local geography is well established. Research on the China shock showed that rising import competition produced sharply different effects across US labour markets because different places began with different industrial structures. Studies of trade reform in Brazil and India reach a similar conclusion: national tariff changes produce sharply different regional effects because places begin with different industrial structures.
This project builds on that insight but applies it to a different problem. Rather than starting with one tariff change or one trading partner, it maps the local economic relationships through which a broader range of geopolitical disruptions could travel.
Partners have different geographies
Partners don’t expose the same places either. Of the four we’ve mapped so far: China, Germany, Russia, Saudi Arabia, each leaves its own fingerprint.
The Geography of Geopolitical Exposure
Export and import exposure identify different local economies
Each point represents a US county. Select a trading partner to compare the geography of export dependence with exposure to import competition.
Light dashed lines in percentile view mark the 50th and 90th percentile thresholds on each axis. In raw and log views, the dashed line is a fitted linear trend.
How exposure is measured
Export specialization
A measure of how disproportionately a county's local economy is oriented toward producing goods that the United States exports to the selected partner, relative to the county's overall size. Counties with a high value depend more heavily, in relative terms, on industries tied to that export relationship.
Import-competition specialization
A parallel measure of how disproportionately a county's local economy is concentrated in industries exposed to import competition from the selected partner. A high value indicates the county's employment base sits in sectors most exposed to that competing trade flow.
Why percentile mode is the default
Both measures are heavily right-skewed: a small number of counties have extreme values driven by a single dominant industry or facility. Percentile ranks, calculated separately for each partner, let readers compare relative standing across the full distribution of counties without a handful of outliers compressing the rest of the chart. Raw and log views are provided for readers who want to see the underlying scale of the data.
What this figure does and does not show
This figure describes underlying economic structure — how exposed a county's industry mix is, in principle, to trade with a given partner. It does not measure realised trade flows, employment changes, or economic outcomes, and it should not be read as evidence of actual impact.
Source: US Census bilateral trade, HS–NAICS concordance and QCEW employment. Data for 2025.
This figure measures exposure, not realised trade or employment effects. No causal claims are implied.
Germany has the most concentrated export exposure among the four when concentration is measured by the share accounted for by the top 10 counties: its top 10 counties account for 10.4 percent of national export specialization, compared with 8.2 percent for Russia, 6.8 percent for China, and 5.4 percent for Saudi Arabia. On the import-competition side, Saudi Arabia is the clear outlier, with 43.5 percent concentrated in its top 10 counties. Russia follows at 13.6 percent, while China and Germany are much more geographically dispersed, at 6.4 percent and 5.6 percent respectively.
The geography of geopolitical exposure
Same partner, different map
For each partner we know exactly three things: how much of the national total sits in the 10 most-exposed counties, the top 25, and the top 50. Toggle between export markets and import competition, then compare those three checkpoints across China, Germany, Russia and Saudi Arabia.
Share of national export specialization
Measured at three checkpoints only · dashed grey ticks mark what an even spread across all 3,250 counties would look like at each checkpoint
Reading the chart: the grey dashed ticks show what each checkpoint would look like if exposure were spread perfectly evenly across all 3,250 counties (N ÷ 3,250). All four partners sit well above that reference at every checkpoint, but by very different margins. Saudi Arabia's import-competition exposure is the outlier: 43.5% of the national total sits in its ten most-exposed counties, rising to 77.6% by the top 50 — in a different league from China, Germany or Russia on that same measure. On the export side, Germany is the most concentrated of the four, not Saudi Arabia.
Also, partner dependence first runs through industries, then through the places where those industries employ workers. Five industries account for 81.3 percent of Germany’s export specialization, led by oil and gas extraction, transportation equipment, chemicals, crop production, and machinery. Saudi Arabia’s import-competition exposure is more extreme: oil and gas extraction alone accounts for 91.1 percent of the measure. Across the partner-channel combinations examined here, exposure is generally more concentrated across industries than across geographical units. The map is therefore showing where the industries underpinning a particular trading relationship are located.
The beef story from the opening is one channel of China exposure in motion. It is an export-market shock, felt most directly in ranching and meat-processing economies across Texas, Kansas, and Nebraska. Import competition from China traces a different industrial and geographic pattern. Combining the two into one “China risk” score would obscure which part of the trade relationship was actually under pressure.
What’s still missing
This first instalment deliberately starts with a small number of relationships with four countries where the underlying event catalogue is already well validated. In the coming instalments, the analysis will expand from a set of individual case studies into a comprehensive geography of US exposure to geopolitical fragmentation.
In addition, exposure is not the same as vulnerability. This analysis does not yet measure how sensitive a county would be to disruption or how readily its firms and workers could adjust. Two counties with similar exposure may therefore experience very different outcomes. Distinguishing exposure from adjustment is precisely why the later instalments examine trade responses, hiring, employment, wages, and rerouting separately.
For now, a key takeaway: if you’re looking at supplier or market risk, don’t trust a single “exposure score”, and don’t assume small or rural means safe.
Where the series goes from here
This article establishes where different international relationships matter within the American economy. The next step is to examine what happens when those relationships begin to deteriorate.
The remaining instalments follow the shock through the economy: when trade and employment start to adjust, whether employers respond first through hiring, headcount or wages, and whether disrupted activity returns to the United States or reroutes elsewhere. The final instalment asks whether these signals can be combined into a practical early-warning framework.
Before asking when geopolitical fragmentation becomes economically visible, we first need to know where it can land. National tensions may begin in capitals, but their economic consequences are ultimately written into local labour markets.
Cover photo by Sean Benesh on Unsplash