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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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Collaborative Micro-productivity Project: Establishment-Level Productivity Dataset, 1972-2020
December 2023
Working Paper Number:
CES-23-65
We describe the process for building the Collaborative Micro-productivity Project (CMP) microdata and calculating establishment-level productivity numbers. The documentation is for version 7 and the data cover the years 1972-2020. These data have been used in numerous research papers and are used to create the experimental public-use data product Dispersion Statistics on Productivity (DiSP).
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Productivity 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.
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Cyclical Worker Flows: Cleansing vs. Sullying
May 2021
Working Paper Number:
CES-21-10
Do recessions speed up or impede productivity-enhancing reallocation? To investigate this question, we use U.S. linked employer-employee data to examine how worker flows contribute to productivity growth over the business cycle. We find that in expansions high-productivity firms grow faster primarily by hiring workers away from lower-productivity firms. The rate at which job-to-job flows move workers up the productivity ladder is highly procyclical. Productivity growth slows during recessions when this job ladder collapses. In contrast, flows into nonemployment from low productivity firms disproportionately increase in recessions, which leads to an increase in productivity growth. We thus find evidence of both sullying and cleansing effects of recessions, but the timing of these effects differs. The cleansing effect dominates early in downturns but the sullying effect lingers well into the economic recovery.
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The Micro-Level Anatomy of the Labor Share Decline
March 2020
Working Paper Number:
CES-20-12
The labor share in U.S. manufacturing declined from 62 percentage points (ppts) in 1967 to 41 ppts in 2012. The labor share of the typical U.S. manufacturing establishment, in contrast, rose by over 3 ppts during the same period. Using micro-level data, we document five salient facts: (1) since the 1980s, there has been a dramatic reallocation of value added toward the lower end of the labor share distribution; (2) this aggregate reallocation is not due to entry/exit, to 'superstars" growing faster or to large establishments lowering their labor shares, but is instead due to units whose labor share fell as they grew in size; (3) low labor share (LL) establishments benefit from high revenue labor productivity, not low wages; (4) they also enjoy a product price premium relative to their peers, pointing to a significant role for demand-side forces; and (5) they have only temporarily lower labor shares that rebound after five to eight years. This transient pattern has become more pronounced over time, and the dynamics of value added and employment are increasingly disconnected.
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Do Short-Term Incentives Affect Long-Term Productivity?
March 2020
Working Paper Number:
CES-20-10
Previous research shows that stock repurchases that are caused by earnings management lead to reductions in firm-level investment and employment. It is natural to expect firms to cut less productive investment and employment first, which could lead to a positive effect on firm-level productivity. However, using Census data, we find that firms make cuts across the board irrespective of plant productivity. This pattern seems to be associated with frictions in the labor market. Specifically, we find evidence that unionization of the labor force may prevent firms from doing efficient downsizing, forcing them to engage in easy or expedient downsizing instead. As a result of this inefficient downsizing, EPS-driven repurchases lead to a reduction in long-term productivity.
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Automation, Labor Share, and Productivity:
Plant-Level Evidence from U.S. Manufacturing
September 2018
Working Paper Number:
CES-18-39
This paper provides new evidence on the plant-level relationship between automation, labor and capital usage, and productivity. The evidence, based on the U.S. Census Bureau's Survey of Manufacturing Technology, indicates that more automated establishments have lower production labor share and higher capital share, and a smaller fraction of workers in production who receive higher wages. These establishments also have higher labor productivity and experience larger long-term labor share declines. The relationship between automation and relative factor usage is modelled using a CES production function with endogenous technology choice. This deviation from the standard Cobb-Douglas assumption is necessary if the within-industry differences in the capital-labor ratio are determined by relative input price differences. The CES-based total factor productivity estimates are significantly different from the ones derived under Cobb-Douglas production and positively related to automation. The results, taken together with earlier findings of the productivity literature, suggest that the adoption of automation may be one mechanism associated with the rise of superstar firms.
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Dispersion in Dispersion: Measuring Establishment-Level Differences in Productivity
April 2018
Working Paper Number:
CES-18-25RR
We describe new experimental productivity statistics, Dispersion Statistics on Productivity (DiSP), jointly developed and published by the Bureau of Labor Statistics (BLS) and the Census Bureau. Productivity measures are critical for understanding economic performance. Official BLS productivity statistics, which are available for major sectors and detailed industries, provide information on the sources of aggregate productivity growth. A large body of research shows that within-industry variation in productivity provides important insights into productivity dynamics. This research reveals large and persistent productivity differences across businesses even within narrowly defined industries. These differences vary across industries and over time and are related to productivity-enhancing reallocation. Dispersion in productivity across businesses can provide information about the nature of competition and frictions within sectors, and about the sources of rising wage inequality across businesses. Because there were no official statistics providing this level of detail, BLS and the Census Bureau partnered to create measures of within-industry productivity dispersion. These measures complement official BLS aggregate and industry-level productivity growth statistics and thereby improve our understanding of the rich productivity dynamics in the U.S. economy. The underlying microdata for these measures are available for use by qualified researchers on approved projects in the Federal Statistical Research Data Center (FSRDC) network. These new statistics confirm the presence of large productivity differences and we hope that these new data products will encourage further research into understanding these differences.
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Strong Employers and Weak Employees:
How Does Employer Concentration Affect Wages?
April 2018
Working Paper Number:
CES-18-15
We analyze the effect of local-level labor market concentration on wages. Using plant-level U.S. Census data over the period 1977'2009, we find that: (1) local-level employer concentration exhibits substantial cross-sectional and time-series variation and increases over time; (2) consistent with labor market monopsony power, there is a negative relation between local-level employer concentration and wages that is more pronounced at high levels of concentration and increases over time; (3) the negative relation between labor market concentration and wages is stronger when unionization rates are low; (4) the link between productivity growth and wage growth is stronger when labor markets are less concentrated; and (5) exposure to greater import competition from China (the 'China Shock') is associated with more concentrated labor markets. These five results emphasize the role of local-level labor market monopsonies in influencing firm wage-setting.
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Hours Off the Clock
January 2017
Working Paper Number:
CES-17-44
To what extent do workers work more hours than they are paid for? The relationship
between hours worked and hours paid, and the conditions under which employers can demand more hours 'off the clock,' is not well understood. The answer to this question impacts worker welfare, as well as wage and hour regulation. In addition, work off the clock has important implications for the measurement and cyclical movement of productivity and wages. In this paper, I construct a unique administrative dataset of hours paid by employers linked to a survey of workers on their reported hours worked to measure work off the clock. Using cross-sectional variation in local labor markets, I find only a small cyclical component to work off the clock. The results point to labor hoarding rather than efficiency wage theory, indicating work off the clock cannot explain the counter-cyclical movement of productivity. I find workers employed by small firms, and in industries with a high rate of wage and hour violations are associated with larger differences in hours worked than hours paid. These findings suggest the importance of tracking hours of work for enforcement of labor regulations.
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