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Automation and the Workforce: A Firm-Level View from the 2019 Annual Business Survey
April 2022
Authors:
John Haltiwanger,
Lucia Foster,
Emin Dinlersoz,
Nikolas Zolas,
Daron Acemoglu,
Catherine Buffington,
Nathan Goldschlag,
Zachary Kroff,
David Beede,
Gary Anderson,
Eric Childress,
Pascual Restrepo
Working Paper Number:
CES-22-12R
This paper describes the adoption of automation technologies by US firms across all economic sectors by leveraging a new module introduced in the 2019 Annual Business Survey, conducted by the US Census Bureau in partnership with the National Center for Science and Engineering Statistics (NCSES). The module collects data from over 300,000 firms on the use of five advanced technologies: AI, robotics, dedicated equipment, specialized software, and cloud computing. The adoption of these technologies remains low (especially for AI and robotics), varies substantially across industries, and concentrates on large and young firms. However, because larger firms are much more likely to adopt them, 12-64% of US workers and 22-72% of manufacturing workers are exposed to these technologies. Firms report a variety of motivations for adoption, including automating tasks previously performed by labor. Consistent with the use of these technologies for automation, adopters have higher labor productivity and lower labor shares. In particular, the use of these technologies is associated with a 11.4% higher labor productivity, which accounts for 20'30% of the difference in labor productivity between large firms and the median firm in an industry. Adopters report that these technologies raised skill requirements and led to greater demand for skilled labor, but brought limited or ambiguous effects to their employment levels.
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Advanced Technologies Adoption and Use by U.S. Firms: Evidence from the Annual Business Survey
December 2020
Working Paper Number:
CES-20-40
We introduce a new survey module intended to complement and expand research on the causes and consequences of advanced technology adoption. The 2018 Annual Business Survey (ABS), conducted by the Census Bureau in partnership with the National Center for Science and Engineering Statistics (NCSES), provides comprehensive and timely information on the diffusion among U.S. firms of advanced technologies including artificial intelligence (AI), cloud computing, robotics, and the digitization of business information. The 2018 ABS is a large, nationally representative sample of over 850,000 firms covering all private, nonfarm sectors of the economy. We describe the motivation for and development of the technology module in the ABS, as well as provide a first look at technology adoption and use patterns across firms and sectors. We find that digitization is quite widespread, as is some use of cloud computing. In contrast, advanced technology adoption is rare and generally skewed towards larger and older firms. Adoption patterns are consistent with a hierarchy of increasing technological sophistication, in which most firms that adopt AI or other advanced business technologies also use the other, more widely diffused technologies. Finally, while few firms are at the technology frontier, they tend to be large so technology exposure of the average worker is significantly higher. This new data will be available to qualified researchers on approved projects in the Federal Statistical Research Data Center network.
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Upstream, Downstream: Diffusion and Impacts of the Universal Product Code
January 2017
Working Paper Number:
CES-17-66R
We study the adoption, diffusion, and impacts of the Universal Product Code (UPC) between 1975 and 1992, during the initial years of the barcode system. We find evidence of network effects in the diffusion process. Matched-sample difference-in-difference estimates show that firm size and trademark registrations increase following UPC adoption by manufacturers. Industry-level import penetration also increases with domestic UPC adoption. Our findings suggest that barcodes, scanning, and related technologies helped stimulate variety-enhancing product innovation and encourage the growth of international retail supply chains.
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Industrial Investments in Energy Efficiency: A Good Idea?
January 2017
Working Paper Number:
CES-17-05
Yes, from an energy-saving perspective. No, once we factor in the negative output and productivity adoption effects. These are the main conclusions we reach by conducting the first large-scale study on cogeneration technology adoption ' a prominent form of energy-saving investments ' in the U.S. manufacturing sector, using a sample that runs from 1982 to 2010 and drawing on multiple data sources from the U.S. Census Bureau and the U.S. Energy Information Administration. We first show through a series of event studies that no differential trends exist in energy consumption nor production activities between adopters and never-adopters prior to the adoption event. We then compute a distribution of realized returns to energy savings, using accounting methods and regression methods, based on our difference-in-difference estimator. We find that (1) significant heterogeneity exists in returns; (2) unlike previous studies in the residential sector, the realized and projected returns to energy savings are roughly consistent in the industrial sector, for both private and social returns; (3) however, cogeneration adoption decreases manufacturing output and productivity persistently for at least the next 7-10 years, relative to the control group. Our IV strategies also show sizable decline in TFP post adoption.
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Data in Action: Data-Driven Decision Making in U.S. Manufacturing
January 2016
Working Paper Number:
CES-16-06
Manufacturing in America has become significantly more data-intensive. We investigate the adoption, performance effects and organizational complementarities of data-driven decision making (DDD) in the U.S. Using data collected by the Census Bureau for 2005 and 2010, we observe the extent to which manufacturing firms track and use data to guide decision making, as well as their investments in information technology (IT) and the use of other structured management practices. Examining a representative sample of over 18,000 plans, we find that adoption of DDD is earlier and more prevalent among larger, older plants belonging to multi-unit firms. Smaller single-establishment firms adopt later but have a higher correlation with performance than similar non-adopters. Using a fixed-effects estimator, we find the average value-added for later DDD adopters to be 3% greater than non-adopters, controlling for other inputs to production. This effect is distinct from that associated with IT and other structured management practices and is concentrated among single-unit firms. Performance improves after plants adopt DDD, but not before ' consistent with a causal relationship. However, DDD-related performance differentials decrease over time for early and late adopters, consistent with firm learning and development of organizational complementarities. Formal complementarity tests suggest that DDD and high levels of IT capital reinforce each other, as do DDD and skilled workers. For some industries, the benefits of DDD adoption appear to be greater for plants that delegate some decision making to frontline workers.
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The Impact of Information and Communication Technology Adoption on Multinational Firm Boundary Decisions
January 2016
Working Paper Number:
CES-16-01
This paper evaluates the effect of adopting internet-enabled information and communication technology (ICT) adoption on the decision to reorganize production across national borders (foreign boundary decision) by multinational enterprises (MNE). Using a transaction cost framework, we argue that ICT adoption influences foreign boundary decisions by lowering coordination costs both internally and externally for the firm. We propose that the heterogeneity in the technology's characteristics, namely complexity and the production processes' degree of codifiability, moderate this influence. Using a difference-in-differences methodology and exploiting the richness of confidential U.S. Census Bureau microdata, we find that overall ICT adoption is positively associated with greater likelihood of in-house production, as measured by increases in intra-firm trade shares. Furthermore, we find that more complex forms of ICT are associated with larger increases in intra-firm trade shares. Finally, our results indicate that MNEs in industries in which production specifications are more easily codified in an electronic format are less likely to engage in intra-firm relative to arms-length trade following ICT adoption.
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Technology and Production Fragmentation: Domestic versus Foreign Sourcing
January 2013
Working Paper Number:
CES-13-35R
This paper provides direct empirical evidence on the relationship between technology and firms' global sourcing strategies. Using new data on U.S. firms' decisions to contract for manufacturing services from domestic or foreign suppliers, I show that a firm's adoption of communication technology between 2002 to 2007 is associated with a 3.1 point increase in its probability of fragmentation. The effect of firm technology also differs significantly across industries; in 2007, it is 20 percent higher, relative to the mean, in industries with production specifications that are easier to codify in an electronic format. These patterns suggest that technology lowers coordination costs, though its effect is disproportionately higher for domestic rather than foreign sourcing. The larger impact on domestic fragmentation highlights its importance as an alternative to offshoring, and can be explained by complementarities between technology and worker skill. High technology firms and industries are more likely to source from high human capital countries, and the differential impact of technology across industries is strongly increasing in country human capital.
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Do Market Leaders Lead in Business Process Innovation? The Case(s) of E-Business Adoption
April 2011
Working Paper Number:
CES-11-10
This paper investigates the relationship between market position and the adoption of IT-enabled process innovations. Prior research has focused overwhelmingly on product innovation and garnered mixed empirical support. I extend the literature into the understudied area of business process innovation, developing a framework for classifying innovations based on the complexity, interdependence, and customer impact of the underlying business process. I test the framework's predictions in the context of ebuying and e-selling adoption. Leveraging detailed U.S. Census data, I find robust evidence that market leaders were significantly more likely to adopt the incremental innovation of e-buying but commensurately less likely to adopt the more radical practice of e-selling. The findings highlight the strategic significance of adjustment costs and co-invention capabilities in technology adoption, particularly as businesses grow more dependent on new technologies for their operational and competitive performance.
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Electronic Networking Technologies, Innovation Misfit, and Plant Performance
February 2010
Working Paper Number:
CES-10-03
Prior work on information technology (IT) adoption and economic impacts typically employs an instrumental logic in which firms lead with innovation when they possess characteristics that make it economically beneficial to do so and lag when they do not. However, firms may deviate from this idealized picture when they possess characteristics of an innovation laggard but exhibit the behavior of an innovation leader (or vice versa), with implications for the returns to IT investment. This study develops a conceptual framework and hypotheses regarding the implications of such deviations, which we call innovation misfits. Using a data set comprising measures of the adoption of electronic networking technologies (ENT) in over 25,000 U.S. manufacturing plants, productivity regression estimation reveals a consistent pattern that the association between IT and productivity is diminished in the presence of innovation misfit. We discuss the implications of innovation misfit for scholarship and management practice, which are numerous.
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Technology Use and Worker Outcomes: Direct Evidence from Linked Employee-Employer Data
August 2000
Working Paper Number:
CES-00-13
We investigate the impact of technology adoption on workers' wages and mobility in U.S. manufacturing plants by constructing and exploiting a unique Linked Employee-Employer data set containing longitudinal worker and plant information. We first examine the effect of technology use on wage determination, and find that technology adoption does not have a significant effect on high-skill workers, but negatively affects the earnings of low-skill workers after controlling for worker-plant fixed effects. This result seems to support the skill-biased technological change hypothesis. We next explore the impact of technology use on worker mobility, and find that mobility rates are higher in high-technology plants, and that high-skill workers are more mobile than their low and medium-skill counterparts. However, our technology-skill interaction term indicates that as the number of adopted technologies increases, the probability of exit of skilled workers decreases while that of unskilled workers increases.
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