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An Anatomy of U.S. Establishments' Trade Linkages in Global Value Chains
June 2025
Working Paper Number:
CES-25-44
Global value chains (GVC) are a pervasive feature of modern production, but they are hard to measure. Using confidential microdata from the U.S. Census Bureau, we develop novel measures of the linkages between U.S. manufacturing establishments' imports and exports. We find that for every dollar of exports, imported inputs represent 13 cents in 2002 and 20 cents by 2017. Examining GVC trade flows in a gravity framework, we find that these flows are higher within 'round-trip' (input and output market is the same) linkages, regional trade agreements, and multinational firm boundaries. The strong complementarities between input and output markets are muted by the proportionality assumptions embedded in global input-output tables. Finally, with an off-the-shelf model, we show the round-trip results can be obtained when firm-specific sourcing and exporting fixed costs are linked.
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Investments under Risk: Evidence from Hurricane Strikes
June 2025
Working Paper Number:
CES-25-43
We demonstrate that firms with plants in areas subject to a significant hurricane strike reduce their capital expenditures at the hurricane-affected plants and shift capital expenditures to plants in non-hurricane-affected areas. This effect is not present prior to 1997 and only appears from 1997 on. Our evidence is consistent with the possibility that a significant climate event such as the signing of the Kyoto Protocol raised the salience of the perceived risk from actual hurricane strikes and shifted firm behavior.
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The Rise of Industrial AI in America: Microfoundations of the Productivity J-curve(s)
April 2025
Working Paper Number:
CES-25-27
We examine the prevalence and productivity dynamics of artificial intelligence (AI) in American manufacturing. Working with the Census Bureau to collect detailed large-scale data for 2017 and 2021, we focus on AI-related technologies with industrial applications. We find causal evidence of J-curve-shaped returns, where short-term performance losses precede longer-term gains. Consistent with costly adjustment taking place within core production processes, industrial AI use increases work-in-progress inventory, investment in industrial robots, and labor shedding, while harming productivity and profitability in the short run. These losses are unevenly distributed, concentrating among older businesses while being mitigated by growth-oriented business strategies and within-firm spillovers. Dynamics, however, matter: earlier (pre-2017) adopters exhibit stronger growth over time, conditional on survival. Notably, among older establishments, abandonment of structured production-management practices accounts for roughly one-third of these losses, revealing a specific channel through which intangible factors shape AI's impact. Taken together, these results provide novel evidence on the microfoundations of technology J-curves, identifying mechanisms and illuminating how and why they differ across firm types. These findings extend our understanding of modern General Purpose Technologies, explaining why their economic impact'exemplified here by AI'may initially disappoint, particularly in contexts dominated by older, established firms.
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The Effect of Oil News Shocks on Job Creation and Destruction
January 2025
Working Paper Number:
CES-25-06
Using data from the Annual Survey of Manufactures (ASM) and the Census of Manufacturing (CMF), we construct quarterly measures of job creation and destruction by 3-digit NAICS industries spanning from 1980Q3-2016Q4. These long series allow us to address three questions regarding the effect of oil news shocks. What is the average effect of oil news shocks on sectoral labor reallocation? What characteristics explain the observed heterogeneity in the average responses across industries? Has the response of US manufacturing changed over time? We find evidence that oil news shocks exert only a moderate effect on total manufacturing net employment growth but lead to a significant increase in job reallocation. However, we find a high degree of heterogeneity in responses across industries. We then show that the cross-industry variation in the sensitivity of net employment growth and excess job reallocation to oil news shocks is related to differences in energy costs, the rate of energy to capital expenditures, and the share of mature firms in the industry. Finally, we illustrate how the dynamic response of sectoral job creation and destruction to oil news shocks has declined since the mid-2000s.
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Multinational Production and Innovation in Tandem
October 2024
Working Paper Number:
CES-24-64
Multinational firms colocate production and innovation by offshoring them to the same host country or region. In this paper, I examine the determinants of multinational firms' production and innovation locations. Exploiting plausibly exogenous variations in tariffs, I find complementarities between production and innovation within host countries and regions. To evaluate manufacturing reshoring policies, I develop a quantitative multicountry offshoring location choice model. I allow for rich colocation benefits and cross-country interdependencies and prove supermodularity of the model to solve this otherwise NP-hard problem. I find the effects of manufacturing reshoring policies are nonlinear, contingent upon firm heterogeneity, and they accumulate dynamically.
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Entry Costs Rise with Growth
October 2024
Working Paper Number:
CES-24-63
Over time and across states in the U.S., the number of firms is more closely tied to overall employment than to output per worker. In many models of firm dynamics, trade, and growth with a free entry condition, these facts imply that the costs of creating a new firm increase sharply with productivity growth. This increase in entry costs can stem from the rising cost of labor used in entry and weak or negative knowledge spillovers from prior entry. Our findings suggest that productivity-enhancing policies will not induce firm entry, thereby limiting the total impact of such policies on welfare.
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Aggregation Bias in the Measurement of U.S. Global Value Chains
September 2024
Working Paper Number:
CES-24-49
This paper measures global value chain (GVC) activity, defined as imported content of exports, of U.S. manufacturing plants between 2002 and 2012. We assesses the extent of aggregation bias that arises from relying on industry-level exports, imports, and output to establish three results. First, GVC activity based on industry-level data underestimate the actual degree of GVC engagement by ignoring potential correlations between import and export activities across plants within industries. Second, the bias grew over the sample period. Finally, unlike with industry-level measures, we find little slowdown in GVC integration by U.S. manufacturers.
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Empirical Distribution of the Plant-Level Components of Energy and Carbon Intensity at the Six-digit NAICS Level Using a Modified KAYA Identity
September 2024
Working Paper Number:
CES-24-46
Three basic pillars of industry-level decarbonization are energy efficiency, decarbonization of energy sources, and electrification. This paper provides estimates of a decomposition of these three components of carbon emissions by industry: energy intensity, carbon intensity of energy, and energy (fuel) mix. These estimates are constructed at the six-digit NAICS level from non-public, plant-level data collected by the Census Bureau. Four quintiles of the distribution of each of the three components are constructed, using multiple imputation (MI) to deal with non-reported energy variables in the Census data. MI allows the estimates to avoid non-reporting bias. MI also allows more six-digit NAICS to be estimated under Census non-disclosure rules, since dropping non-reported observations may have reduced the sample sizes unnecessarily. The estimates show wide variation in each of these three components of emissions (intensity) and provide a first empirical look into the plant-level variation that underlies carbon emissions.
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Competition, Firm Innovation, and Growth under Imperfect Technology Spillovers
July 2024
Working Paper Number:
CES-24-40
We study how friction in learning others' technology, termed 'imperfect technology spillovers,' incentivizes firms to use different types of innovation and impacts the implications of competition through changes in innovation composition. We build an endogenous growth model in which multi-product firms enhance their products via internal innovation and enter new product markets through external innovation. When learning others' technology takes time due to this friction, increased competitive pressure leads firms with technological advantages to intensify internal innovation to protect their markets, thereby reducing others' external innovation. Using the U.S. administrative firm-level data, we provide regression results supporting the model predictions. Our findings highlight the importance of strategic firm innovation choices and changes in their composition in shaping the aggregate implications of competition.
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The Rise of Specialized Firms
February 2024
Working Paper Number:
CES-24-06
This paper studies firm diversification over 6-digit NAICS industries in U.S. manufacturing. We find that firms specializing in fewer industries now account for a substantially greater share of production than 40 years ago. This reallocation is a key driver of rising industry concentration. Specialized firms have displaced diversified firms among industry leaders'absent this reallocation concentration would have decreased. We then provide evidence that specialized firms produce higher-quality goods: specialized firms tend to charge higher unit prices and are more insulated against Chinese import competition. Based on our empirical findings, we propose a theory in which growth shifts demand toward specialized, high-quality firms, which eventually increases concentration. We conclude that one should expect rising industry concentration in a growing economy.
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