National-security restrictions on exports constrain exporters' market access, but empirical evidence on their domestic costs is limited. We leverage data on export transactions that includes the product classifications used to administer U.S. export controls to document a doubling in the share of U.S. exports subject to controls between 2010 and 2024 and a skewed firm-size distribution among firms that export controlled products. We then exploit the 2014 U.S. restriction on exports to Russia as a natural experiment to examine the impact of export controls on firm-level outcomes. These controls not only reduced U.S. firms' probability of exporting targeted goods to Russia but also had indirect effects: they reduced affected firms' exports of other products and to other destinations and lowered affected firms' average payroll. Our findings imply that the domestic costs of export controls extend beyond direct restrictions.
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Food Fight: U.S. Exporters' Adjustments to Russia's 2014 Agricultural Import Ban
December 2025
Working Paper Number:
CES-25-79
This paper examines the impact of Russia's 2014 food-import ban on U.S. firms that exported banned products to Russia. Using confidential customs transaction data, we implement triple-difference and dosage-response approaches to identify how firms adjust to the sudden loss of a market. Following the ban, treated firms experienced a 30 percentage-point decrease in the probability of exporting banned food to Russia relative to control firms. However, there is substantial heterogeneity by pre-ban reliance on the Russian market: heavily reliant firms were significantly less likely to survive once the ban was in place, and survivors experienced large reductions in revenue (19%) and total export value (49%) for each standard deviation increase in Russian market exposure. We find evidence of export redirection to neighboring countries, though it is insufficient to offset losses. Any negative impacts on survivors dissipate by five years post-ban.
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The U.S. Multinational Advantage during the 2008-2009 Financial Crisis: The Role of Services Trade
January 2026
Working Paper Number:
CES-26-04
We document the augmenting role of services exports in U.S. multinationals' goods-export growth during the global financial crisis. Using newly linked data on U.S. firms' foreign sales of goods and services and a triple-difference identification strategy combined with propensity-score matching, we find that compared to multinationals that only export goods (mono-exporters), multinationals that also export services to the same destination (bi-exporters) experienced higher goods-export growth. This result is driven by sales of intellectual property rights related to industrial processes (e.g., patents, trademarks). We also find higher growth in bi-exporters' foreign affiliate services sales and domestic employment in services sectors. These results reveal a pivotal role of services exports in supporting foreign demand for U.S. goods during the crisis.
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The Microstructure of AI Diffusion: Evidence From Firms, Business Functions, and Worker Tasks
April 2026
Working Paper Number:
CES-26-25
Using novel, nationally representative data from the 2026 AI supplement to the U.S. Census Bureau's Business Trends and Outlook Survey (BTOS), we characterize AI diffusion across three interconnected layers: overall firm use, deployment across business functions, and worker-task use. This multi-layered approach provides a nuanced picture of business AI adoption. During the supplement reference period (Nov 2025-Jan 2026), 18% of firms used AI in a business function, rising to 32% on an employment-weighted basis; adoption is expected to reach 22% within six months. AI use is substantially higher in large firms and knowledge-intensive sectors, with use rates reaching 50%-60% (60%-70%, employment-weighted) for very large firms in the Information, Professional Services, and Finance sectors. Among adopting firms, the scope of use remains limited: 57% of users integrate AI in three or fewer business functions, most commonly Sales and Marketing (52%), Strategy and Business Development (45%), and IT (41%). In 23% (41%, employment-weighted) of firms, workers use AI in work-related tasks. Writing, document analysis, and information search are the leading Generative AI use in tasks, though 65% of firms limit use to three or fewer tasks. The evidence points to both top-down and bottom-up diffusion channels: worker task use sometimes occurs without formal firm-level adoption, and firm-level adoption sometimes occurs without worker task use. Most users (66%) rely on AI solely to augment tasks, while AI-related employment decreases are rare, occurring in only 2% of firms. Regression analysis shows a robust positive correlation between firm commercial performance and the breadth of AI integration, including functional deployment, task-level use, and operational investment. A distinct divergence emerges, however, with respect to labor outcomes. Functional breadth and operational investment are positively associated with employment decreases, whereas worker-task integration shows no significant link to headcount reduction once functional integration and operational investment are taken into account.
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Recall and Response: Relationship Adjustments to Adverse Information Shocks
March 2020
Working Paper Number:
CES-20-13R
How resilient are U.S. buyer-foreign supplier relationships to new information about product defects? We construct a novel dataset of U.S. consumer-product recalls sourced from foreign suppliers between 1995 and 2013. Using an event-study approach, we find that compared to control relationships, buyers that experience recalls temporarily reduce their probability of trading with the suppliers of the recalled products by 17%. The reduction is much larger for new than established buyer'supplier relationships. Buyers that experience a recall are more likely to add other suppliers to their portfolios, diversifying supplier-specific risk in the aftermath of a recall; this effect, too, is larger for buyers impacted by recalls in new relationships. There is a long lag ' up to two years ' before diversification, consistent with a high cost of establishing new relationships.
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Rising Import Tariffs, Falling Export Growth: When Modern Supply Chains Meet Old-Style Protectionism
January 2020
Working Paper Number:
CES-20-01
We examine the impacts of the 2018-2019 U.S. import tariff increases on U.S. export growth through the lens of supply chain linkages. Using 2016 confidential firm-trade linked data, we document the implied incidence and scope of new import tariffs. Firms that eventually faced tariff increases on their imports accounted for 84% of all exports and represented 65% of manufacturing employment. For all affected firms, the implied cost is $900 per worker in new duties. To estimate the effect on U.S. export growth, we construct product-level measures of import tariff exposure of U.S. exports from the underlying firm micro data. More exposed products experienced 2 percentage point lower growth relative to products with no exposure. The decline in exports is equivalent to an ad valorem tariff on U.S. exports of almost 2% for the typical product and almost 4% for products with higher than average exposure.
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How Shocks Travel: the Cross-Border Impact of Natural Disasters in Firm Networks
August 2026
Working Paper Number:
CES-26-55
Do the boundaries of the multinational firm shape how shocks propagate through global production networks? We link U.S. Bill of Lading microdata, geocoded natural disaster records, and cross-border ownership data to trace the transmission of exogenous supply disruptions from foreign suppliers to U.S. importers. Exploiting the quasi-random timing and location of natural disasters in a staggered event-study design, we document that disasters abroad generate sharp, persistent export declines at affected suppliers'shocks that propagate downstream, reducing the growth rate of U.S. importers' total purchases by up to 25 percentage points. Transmission, however, is far from uniform: non-MNC buyers contract roughly twice as much as importers belonging to global corporations, and a comparable gap separates arm's-length from intra-firm trade. These patterns point to the internal networks of multinational firms as shock absorbers that attenuate and redirect supply-side disruptions'suggesting that firm boundaries are not merely organizational choices, but also determinants of macroeconomic resilience.
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Supply Chain Adjustments to Tariff Shocks: Evidence from Firm Trade Linkages in the 2018-2019 U.S. Trade War
August 2024
Working Paper Number:
CES-24-43
We use the 2018-2019 U.S. trade war to examine how supply chains adjustments to a tariff cost shock affect imports and exports. Using confidential firm-trade linked data, we show that the decline in imports of tariffed goods was driven by discontinuations of U.S. buyer'foreign supplier relationships, reduced formation of new relationships, and exits by U.S. firms from import markets altogether. However, tariffed products where imports were concentrated in fewer suppliers had a smaller decline in import growth. We then construct measures of export exposure to import tariffs by linking tariffs paid by importing firms to their exported products. We find that the most exposed products had lower exports in 2018-2019, with most of the impact occurring in 2019.
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Importers, Exporters, and Multinationals: A Portrait of Firms in the U.S. that Trade Goods
October 2005
Working Paper Number:
CES-05-20
This paper provides an integrated view of globally engaged U.S. firms by exploring a newly developed dataset that links U.S. international trade transactions to longitudinal data on U.S. enterprises. These data permit examination of a number of new dimensions of firm activity, including how many products firms trade, how many countries firms trade with, the characteristics of those countries, the concentration of trade across firms, whether firms transact at arms length or with related parties, and whether firms import as well as export. Firms that trade goods play an important role in the U.S., employing more than a third of the U.S. workforce. We find that the most globally engaged U.S. firms, i.e. those that both export to and import from related parties, dominate U.S. trade flows and employment at trading firms. We also find that firms that begin trading between 1993 and 2000 experience especially rapid employment growth and are a major force in overall job creation.
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AI Exposure and Adoption Among U.S. Firms
September 2026
Authors:
John Haltiwanger,
Lucia Foster,
Martha Stinson,
Emin Dinlersoz,
Cheryl Grim,
Zoltan Wolf,
Sabrina Wulff Pabilonia,
Matthew Dey,
Sean Wang,
Aditya Pande,
Peter B. Meyer
Working Paper Number:
CES-26-61
Measures of exposure to artificial intelligence (AI) are widely used to study where AI is likely to affect firm and worker outcomes, yet limited evidence exists on how closely exposure relates to realized AI adoption at the firm level. We examine this relationship by linking 14 firm-level exposure measures, constructed from occupational exposure estimates in the literature and occupational employment shares from the Bureau of Labor Statistics Occupational Employment and Wage Statistics program, to direct measures of firm AI adoption from the Census Bureau's Business Trends and Outlook Survey. Exposure is positively and statistically significantly associated with adoption, but explains only a modest share of its variation. The strength of the relationship varies considerably across standardized exposure measures: a one-standard-deviation increase in firm-level exposure is associated with a 4'11 percentage point higher firm adoption probability, falling to 1'8 percentage points after controlling for year and sub-sector fixed effects. The exposure'adoption relationship is also heterogeneous across firm-size classes and sectors. Exposure is thus an informative but incomplete signal of adoption. More broadly, the results have implications for the interpretation of exposure-based measures in studies of the economic effects of AI.
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Graduating Into Disruption: Labor Market Outcomes for AI-Exposed College Majors
September 2026
Working Paper Number:
CES-26-56
How are new college graduates affected by the rise of artificial intelligence, and what can this tell us about the mechanisms behind AI's overall labor market effects? We use administrative records on college graduates to observe how economic outcomes among college majors with differing levels of labor market AI exposure have evolved since large language models became available. We find that post-graduation employment, earnings, and job switching patterns among the most AI-exposed college majors began to diverge immediately following the introduction of ChatGPT in late 2022. In regression-adjusted estimates, the most AI-exposed decile of college majors saw their likelihood of initial employment decline by five percentage points, while full-quarter initial earnings declined by thirteen percent. This earnings decline is comparable in magnitude to the earnings losses associated with graduating into a large recession. Roughly half of the decline in earnings is attributable to lower earnings within the industry sectors that employ these graduates, with the remainder resulting from a shift in the industry mix into lower-wage sectors such as restaurants and retail. The effects attenuate as graduates move further from labor market entry but remain substantial for the most exposed majors.
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