We use plant-level data from the US Census of Manufacturers to study the short and long run effects of temperature on manufacturing activity. We document that temperature shocks significantly increase energy costs and lower the productivity of small manufacturing plants, while large plants are mostly unaffected. In US counties that experienced higher increases in average temperatures between the 1980s and the 2010s, these heterogeneous effects have led to higher concentration of manufacturing activity within large plants, and a reallocation of labor from small to large manufacturing establishments. We offer a preliminary discussion of potential mechanisms explaining why large manufacturing firms might be better equipped for long-run adaptation to climate change, including their ability to hedge across locations, easier access to finance, and higher managerial skills.
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Technology Lock-In and Costs of Delayed Climate Policy
July 2023
Working Paper Number:
CES-23-33
This paper studies the implications of current energy prices for future energy efficiency and climate policy. Using U.S. Census microdata and quasi-experimental variation in energy prices, we first show that manufacturing plants that open when electricity prices are low consume more energy throughout their lifetime, regardless of current electricity prices. We then estimate that a persistent bias of technological change toward energy can explain the long-term effects of entry-year electricity prices on energy intensity. Overall, this 'technology lock-in' implies that increasing entry-year electricity prices by 10% would decrease a plant's energy intensity of production by 3% throughout its lifetime.
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Returns to Scale in Small and Large U.S. Manufacturing Establishments
September 1990
Working Paper Number:
CES-90-11
The objective of this study is to assess the possibility of differences in the production technologies between large and small establishments in five selected 4-digit SIC manufacturing industries. We particularly focus on estimating returns to scale and then make interferences regarding the efficiency of small businesses relative to large businesses. Using cross-section data for two census years, 1977 and 1982, we estimate a transcendental logarithmic (translog) production model that provides direct estimates of economies of scale parameters for both small and large establishments. Our primary findings are: (i) there are significant differences in the production technologies between small and large establishments; and (ii) based on the scale parameter estimates, small establishments appear to be as efficient as large establishments under normal economic conditions, suggesting that large size is not a necessary condition for efficient production. However, small establishments seem to be unable to maintain constant returns to scale production during economic recession such as that in 1982.
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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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Assessing Multi-Dimensional Performance: Environmental and Economic Outcomes
May 2005
Working Paper Number:
CES-05-03
This study examines the determinants of environmental and economic performance for plants in three traditional smoke-stack industries: pulp and paper, oil, and steel. We combine data from Census Bureau and EPA databases and Compustat on the economic performance, regulatory activity and environmental performance on air and water pollution emissions and toxic releases. We find that plants with higher labor productivity tend to have lower emissions. Regulatory enforcement actions (but not inspections) are associated with lower emissions, and state-level political support for environmental issues is associated with lower water pollution and toxic releases. There is little evidence that plants owned by larger firms perform better, nor do older plants perform worse.
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Local Environmental Regulation and Plant-Level Productivity
September 2010
Working Paper Number:
CES-10-30R
This paper examines the impact of environmental regulation on the productivity of manufacturing plants in the United States. Establishment-level data from three Censuses of Manufactures are used to estimate 3-factor Cobb-Douglas production functions that include a measure of the stringency of environmental regulation faced by manufacturing plants. In contrast to previous studies, this paper examines effects on plants in all manufacturing industries, not just those in 'dirty' industries. Further, this paper employs spatial-temporal variation in environmental compliance costs to identify effects, using a time-varying county-level index that is based on multiple years of establishment-level data from the Pollution Abatement Costs and Expenditures survey and the Annual Survey of Manufactures. Results suggest that, for the average manufacturing plant, the effect on productivity of being in a county with higher environmental compliance costs is relatively small and often not statistically significant. For the average plant, the main effect of environmental regulation may not be in the spatial and temporal dimensions.
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When Do Firms Shift Production Across States to Avoid Environmental Regulation?
December 2001
Working Paper Number:
CES-01-18
This paper examines whether a firm's allocation of production across its plants responds to the environmental regulation faced by those plants, as measured by differences in stringency across states. We also test whether sensitivity to regulation differs based on differences across firms in compliance behavior and/or differences across states in industry importance and concentration. We use Census data for the paper and oil industries to measure the share of each state in each firm's production during the 1967-1992 period. We use several measures of state environmental stringency and test for interactions between regulatory stringency and three factors: the firm's overall compliance rate, a Herfindahl index of industry concentration in the state, and the industry's share in the state economy. We find significant results for the paper industry: firms allocate smaller production shares to states with stricter regulations. This impact is concentrated among firms with low compliance rates, suggesting that low compliance rates are due to high compliance costs, not low compliance benefits. The interactions between stringency and industry characteristics are less often significant, but suggest that the paper industry is more affected by regulation where it is larger or more concentrated. Our results are weaker for the oil industry, reflecting either less opportunity to shift production across states or a greater impact of environmental regulation on paper mills.
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Do Conglomerate Firms Allocate Resources Inefficiently?
February 1999
Working Paper Number:
CES-99-11
We develop a profit-maximizing neoclassical of optimal firm size and growth across different industries. The model predicts how conglomerate firms will allocate resources across divisions over the business cycle and how their responses to industry shocks will differ from those of single-segment firms. We test our model and find that growth of conglomerate and single-segment firms is related to neoclassical theory. Conglomerates grow less in a particular segment of their other segments are more productive and if their other segments experience a larger positive demand shock. We find that the growth rates of peripheral segments are very sensitive to relative productivity and that conglomerates sharply cut the growth of unproductive peripheral segments. We do find some evidence consistent with agency problems for conglomerate firms that are broken up. However, the majority of conglomerate firms exhibit growth across business segments that is consistent with optimal behavior.
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The Market for Corporate Assets: Who Engages in Mergers and Asset Sales and are there Efficiency Gains?
September 1999
Working Paper Number:
CES-99-12
We analyze the market for firms, divisions, and plants of manufacturing firms using a large sample of plant-level data for the period 1974-92. There is an active market for corporate assets, with over 7 percent of plants transacted through mergers and asset sales in expansion years in the economy. Transactions through partial firm sales represent more than half of these transactions. The probability of asset sales and full firm transactions is related to firm organization and buyer and seller ex ante productivity. We find that these transactions result in ex post productivity increases especially for asset sales from peripheral divisions of selling firms to main divisions of other buyers. Finally we find that productivity increases are significantly higher the more productive the buying firm. This timing of sales and the pattern of productivity gains suggests that the transactions that occur, especially through asset sales of plants and divisions, tend to improve the allocation of resources and are consistent with a simple neoclassic model of profit maximizing by firms. The decision to participate in the market for corporate assets and the subsequent gains realized from transactions are affected both by firm productivity and firm organization.
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Costs of Air Quality Regulation
July 1999
Working Paper Number:
CES-99-09
This paper explores some costs associated with environmental regulation. We focus on regulation pertaining to ground-level- ozone (O) and its effects on two manufacturing industries - industrial organic chemicals (SIC 2865-9) and miscellaneous plastic products (SIC 308). Both are major emitters of volatile organic compounds (VOC) and nitrogen oxides (NO), the chemical precursors to ozone. Using plant-level data from the Census Bureau's Longitudinal Research Database (LRD), we examine the effects of regulation on the timing and magnitudes of investments by firms and on the impact it has had on their operating costs. As an alternative way to assess costs, we also employ plant-level data from the Pollution Abatement Costs and Expenditures (PACE) survey. Analyses employing average total costs functions reveal that plants' production costs are indeed higher in (heavily-regulated) non-attainment areas relative to (less-regulated) attainment areas. This is particularly true for younger plants, consistent with the notion that regulation is most burdensome for new (rather existing) plants. Cost estimates using PACE data generally reveal lower costs. We also find that new heavily-regulated plants start out much larger than less-regulated plants, but then do not invest as much. Among other things, this highlights the substantial fixed costs involved in obtaining expansion permits. We also discuss reasons why plants may restrict their size.
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Environmental Regulation And Manufacturing Productivity At The Plant Level
March 1993
Working Paper Number:
CES-93-06
This paper presents results for an analysis of plant-level data from three manufacturing industries (paper, oil, and steel). We combine productivity data from the Longitudinal Research Database ( LRD ) with pollution abatement expenditures from the Census Bureau's Pollution Abatement Cost and Expenditures (PACE) survey, as well as regulatory measures taken from datasets maintained by the Environmental Protection Agency. We use data from 1979 to 1985, considering both labor and total factor productivity, both levels and growth rates, and both annual measures and averages over the period. We find a strong connection between regulation and productivity when regulation is measured by compliance costs. More regulated plants have significantly lower productivity levels and slower productivity growth rates than less regulated plants. The magnitude of the impacts are larger than expected: a $1 increase in compliance costs appears to reduce TFP by the equivalent of $3 to $4. Thus, commonly used methods of calculating the impact of regulation on productivity are substantially underestimated. These results are generally consistent across industries and for different estimation methods. Our other measures of regulation (compliance status, enforcement activity, and emissions) show much less consistent results. Higher enforcement, lower compliance, and higher emissions are generally associated with lower productivity levels and slower productivity growth, but the coefficients are rarely significant.
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