Papers Containing Tag(s): 'Annual Survey of Manufactures'
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Viewing papers 21 through 30 of 240
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Working PaperPropagation and Amplification of Local Productivity Spillovers
August 2022
Working Paper Number:
CES-22-32
This paper shows that local productivity spillovers can propagate throughout the economy through the plant-level networks of multi-region firms. Using confidential Census plant-level data, we find that large manufacturing plant openings not only raise the productivity of local plants but also of distant plants hundreds of miles away, which belong to multi-region firms that are exposed to the local productivity spillover through one of their plants. To quantify the significance of plant-level networks for the propagation and amplification of local productivity shocks, we develop and estimate a quantitative spatial model in which plants of multi-region firms are linked through shared knowledge. Counterfactual exercises show that while knowledge sharing through plant-level networks amplifies the aggregate effects of local productivity shocks, it can widen economic disparities between workers and regions in the economy.View Full Paper PDF
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Working PaperAgglomeration Spillovers and Persistence: New Evidence from Large Plant Openings
June 2022
Working Paper Number:
CES-22-21
We use confidential Census microdata to compare outcomes for plants in counties that 'win' a new plant to plants in similar counties that did not to receive the new plant, providing empirical evidence on the economic theories used to justify local industrial policies. We find little evidence that the average highly incentivized large plant generates significant productivity spillovers. Our semiparametric estimates of the overall local agglomeration function indicate that residual TFP is linear for the range of 'agglomeration' densities most frequently observed, suggesting local economic shocks do not push local economies to a new higher equilibrium. Examining changes twenty years after the new plant entrant, we find some evidence of persistent, positive increases in winning county-manufacturing shares that are not driven by establishment births.View Full Paper PDF
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Working PaperAutomation and the Workforce: A Firm-Level View from the 2019 Annual Business Survey
April 2022
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.View Full Paper PDF
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Working PaperCapital Investment and Labor Demand
February 2022
Working Paper Number:
CES-22-04
We study how bonus depreciation, a policy designed to lower the cost of capital, impacted investment and labor demand in the US manufacturing sector. Difference-in-differences estimates using restricted-use US Census Data on manufacturing establishments show that this policy increased both investment and employment, but did not lead to wage or productivity gains. Using a structural model, we show that the primary effect of the policy was to increase the use of all inputs by lowering overall costs of production. The policy further stimulated production employment due to the complementarity of production labor and capital. Supporting this conclusion, we nd that investment is greater in plants with lower labor costs. Our results show that recent policies that incentivize capital investment do not lead manufacturing plants to replace workers with machines.View Full Paper PDF
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Working PaperFirm Finances and Responses to Trade Liberalization: Evidence from U.S. Tariffs on China
November 2021
Working Paper Number:
CES-21-37
This paper examines the relationship between a firm's finances and its response to trade liberalization. Using a landmark change in U.S. tariff policy vis-'-vis Chinese imports and micro level data from the U.S. Census Bureau, I find larger manufacturing job losses in better capitalized firms - those with less leverage and more cash on hand. The effects concentrate in industries where weaker balance sheets are likely to lead to collateral and other borrowing constraints, helping rule out alternative explanations. Finally, domestic manufacturing job losses are not accompanied by greater reductions in sales or aggregate employment, but better capitalized firms do exhibit reduced input costs and increased productivity. These findings point to offshoring as the predominant firm response to trade liberalization and suggest a role for financial capacity in facilitating offshoring investments.View Full Paper PDF
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Working PaperPay, Productivity and Management
September 2021
Working Paper Number:
CES-21-31
Using confidential Census matched employer-employee earnings data we find that employees at more productive firms, and firms with more structured management practices, have substantially higher pay, both on average and across every percentile of the pay distribution. This pay-performance relationship is particularly strong amongst higher paid employees, with a doubling of firm productivity associated with 11% more pay for the highest-paid employee (likely the CEO) compared to 4.7% for the median worker. This pay-performance link holds in public and private firms, although it is almost twice as strong in public firms for the highest-paid employees. Top pay volatility is also strongly related to productivity and structured management, suggesting this performance-pay relationship arises from more aggressive monitoring and incentive practices for top earners.View Full Paper PDF
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Working PaperDeveloping Content for the Management and Organizational Practices Survey-Hospitals (MOPS-HP)
September 2021
Working Paper Number:
CES-21-25
Nationally representative U.S. hospital data does not exist on management practices, which have been shown to be related to both clinical and financial performance using past data collected in the World Management Survey (WMS). This paper describes the U.S. Census Bureau's development of content for the Management and Organizational Practices Survey Hospitals (MOPS-HP) that is similar to data collected in the MOPS conducted for the manufacturing sector in 2010 and 2015 and the 2009 WMS. Findings from cognitive testing interviews with 18 chief nursing officers and 13 chief financial officers at 30 different hospitals across 7 states and the District of Columbia led to using industry-tested terminology, to confirming chief nursing officers as MOPS-HP respondents and their ability to provide recall data, and to eliminating questions that tested poorly. Hospital data collected in the MOPS-HP would be the first nationally representative data on management practices with queries on clinical key performance indicators, financial and hospital-wide patient care goals, addressing patient care problems, clinical team interactions and staffing, standardized clinical protocols, and incentives for medical record documentation. The MOPS-HP's purpose is not to collect COVID-19 pandemic information; however, data measuring hospital management practices prior to and during the COVID-19 pandemic are a byproduct of the survey's one-year recall period (2019 and 2020).View Full Paper PDF
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Working PaperProductivity Dispersion, Entry, and Growth in U.S. Manufacturing Industries
August 2021
Working Paper Number:
CES-21-21
Within-industry productivity dispersion is pervasive and exhibits substantial variation across countries, industries, and time. We build on prior research that explores the hypothesis that periods of innovation are initially associated with a surge in business start-ups, followed by increased experimentation that leads to rising dispersion potentially with declining aggregate productivity growth, and then a shakeout process that results in higher productivity growth and declining productivity dispersion. Using novel detailed industry-level data on total factor productivity and labor productivity dispersion from the Dispersion Statistics on Productivity along with novel measures of entry rates from the Business Dynamics Statistics and productivity growth data from the Bureau of Labor Statistics for U.S. manufacturing industries, we find support for this hypothesis, especially for the high-tech industries.View Full Paper PDF
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Working PaperRedesigning the Longitudinal Business Database
May 2021
Working Paper Number:
CES-21-08
In this paper we describe the U.S. Census Bureau's redesign and production implementation of the Longitudinal Business Database (LBD) first introduced by Jarmin and Miranda (2002). The LBD is used to create the Business Dynamics Statistics (BDS), tabulations describing the entry, exit, expansion, and contraction of businesses. The new LBD and BDS also incorporate information formerly provided by the Statistics of U.S. Businesses program, which produced similar year-to-year measures of employment and establishment flows. We describe in detail how the LBD is created from curation of the input administrative data, longitudinal matching, retiming of economic census-year births and deaths, creation of vintage consistent industry codes and noise factors, and the creation and cleaning of each year of LBD data. This documentation is intended to facilitate the proper use and understanding of the data by both researchers with approved projects accessing the LBD microdata and those using the BDS tabulations.View Full Paper PDF
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Working PaperBusiness-Level Expectations and Uncertainty
December 2020
Working Paper Number:
CES-20-41
The Census Bureau's 2015 Management and Organizational Practices Survey (MOPS) utilized innovative methodology to collect five-point forecast distributions over own future shipments, employment, and capital and materials expenditures for 35,000 U.S. manufacturing plants. First and second moments of these plant-level forecast distributions covary strongly with first and second moments, respectively, of historical outcomes. The first moment of the distribution provides a measure of business' expectations for future outcomes, while the second moment provides a measure of business' subjective uncertainty over those outcomes. This subjective uncertainty measure correlates positively with financial risk measures. Drawing on the Annual Survey of Manufactures and the Census of Manufactures for the corresponding realizations, we find that subjective expectations are highly predictive of actual outcomes and, in fact, more predictive than statistical models fit to historical data. When respondents express greater subjective uncertainty about future outcomes at their plants, their forecasts are less accurate. However, managers supply overly precise forecast distributions in that implied confidence intervals for sales growth rates are much narrower than the distribution of actual outcomes. Finally, we develop evidence that greater use of predictive computing and structured management practices at the plant and a more decentralized decision-making process (across plants in the same firm) are associated with better forecast accuracy.View Full Paper PDF
