We introduce the Business Dynamics Statistics of Human Capital (BDS-HC) tables, a new Census Bureau experimental product that provides public-use statistics on the workforce composition of firms and its relationship to business dynamics. We use administrative W-2 filings to combine population-level worker demographic data with longitudinal business data to estimate the demographic and educational composition of nearly all non-farm employer businesses in the United States between 2006 and 2022. We use this newly constructed data to document the evolution of employment, entry, and exit of employers based on their workforce compositions. We also provide new statistics on the interaction between firm and worker characteristics, including the composition of workers at startup firms. We find substantial changes between 2006 and 2022 in the distribution of employers along several dimensions, primarily driven by changing workforce compositions within continuing firms rather than the reallocation of employment between firms. We also highlight systematic differences in the business dynamics of firms by their workforce compositions, suggesting that different groups of workers face different economic environments due to their employers.
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FIRM AGE AND SIZE IN THE LONGITUDINAL EMPLOYER-HOUSEHOLD DYNAMICS DATA
March 2014
Working Paper Number:
CES-14-16
The Census Bureau's Quarterly Workforce Dynamics (QWI) and OnTheMap now provide detailed workforce statistics by employer age and size. These data allow a first look at the demographics of workers at small and young businesses as well as detailed analysis of how hiring, turnover, job creation/destruction vary throughout a firm's lifespan. Both the QWI and OnTheMap are tabulated from the Longitudinal Employer-Household Dynamics (LEHD) linked employer-employee data. Firm age and size information was added to the LEHD data through integration of Business Dynamics Statistics (BDS) microdata into the LEHD jobs frame. This paper describes how these two new firm characteristics were added to the microdata and how they are tabulated in QWI and OnTheMap
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High-Growth Firms in the United States: Key Trends and New Data Opportunities
March 2024
Working Paper Number:
CES-24-11
Using administrative data from the U.S. Census Bureau, we introduce a new public-use database that tracks activities across firm growth distributions over time and by firm and establishment characteristics. With these new data, we uncover several key trends on high-growth firms'critical engines of innovation and economic growth. First, the share of firms that are high-growth has steadily decreased over the past four decades, driven not only by falling firm entry rates but also languishing growth among existing firms. Second, this decline is particularly pronounced among young and small firms, while the share of high-growth firms has been relatively stable among large and old firms. Third, the decline in high-growth firms is found in all sectors, but the information sector has shown a modest rebound beginning in 2010. Fourth, there is significant variation in high-growth firm activity across states, with California, Texas, and Florida having high shares of high-growth firms. We highlight several areas for future research enabled by these new data.
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The Business Dynamics Statistics: Describing the Evolution of the U.S. Economy from 1978-2019
October 2021
Working Paper Number:
CES-21-33
The U.S. Census Bureau's Business Dynamics Statistics (BDS) provide annual measures of how many businesses begin, end, or continue their operations and the associated job creation and destruction. The BDS is a valuable resource for information on the U.S. economy because of its long time series (1978-2019), its complete coverage (all private sector, non-farm U.S. businesses), and its tabulations for both individual establishments and the firms that own and control them. In this paper, we use the publicly available BDS data to describe the dynamics of the economy over the past 40 years. We highlight the increasing concentration of employment at old and large firms and describe net job creation trends in the manufacturing, retail, information, food/accommodations, and healthcare industry sectors. We show how the spatial distribution of employment has changed, first moving away from the largest cities and then back again. Finally, we show long-run trends for a group of industries we classify as high-tech and explore how the share of employment at small and young firms has changed for this part of the economy.
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Financing, Ownership, and Performance: A Novel, Longitudinal Firm-Level Database
December 2024
Working Paper Number:
CES-24-73
The Census Bureau's Longitudinal Business Database (LBD) underpins many studies of firm-level behavior. It tracks longitudinally all employers in the nonfarm private sector but lacks information about business financing and owner characteristics. We address this shortcoming by linking LBD observations to firm-level data drawn from several large Census Bureau surveys. The resulting Longitudinal Employer, Owner, and Financing (LEOF) database contains more than 3 million observations at the firm-year level with information about start-up financing, current financing, owner demographics, ownership structure, profitability, and owner aspirations ' all linked to annual firm-level employment data since the firm hired its first employee. Using the LEOF database, we document trends in owner demographics and financing patterns and investigate how these business characteristics relate to firm-level employment outcomes.
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Where Has All the Skewness Gone? The Decline in High-Growth (Young) Firms in the U.S.
November 2015
Working Paper Number:
CES-15-43
The pace of business dynamism and entrepreneurship in the U.S. has declined over recent decades. We show that the character of that decline changed around 2000. Since 2000 the decline in dynamism and entrepreneurship has been accompanied by a decline in high-growth young firms. Prior research has shown that the sustained contribution of business startups to job creation stems from a relatively small fraction of high-growth young firms. The presence of these high-growth young firms contributes to a highly (positively) skewed firm growth rate distribution. In 1999, a firm at the 90th percentile of the employment growth rate distribution grew about 31 percent faster than the median firm. Moreover, the 90-50 differential was 16 percent larger than the 50-10 differential reflecting the positive skewness of the employment growth rate distribution. We show that the shape of the firm employment growth distribution changes substantially in the post-2000 period. By 2007, the 90-50 differential was only 4 percent larger than the 50-10, and it continued to exhibit a trend decline through 2011. The reflects a sharp drop in the 90th percentile of the growth rate distribution accounted for by the declining share of young firms and the declining propensity for young firms to be high-growth firms.
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Business Dynamics Statistics for Single-Unit Firms
December 2022
Working Paper Number:
CES-22-57
The Business Dynamics Statistics of Single Unit Firms (BDS-SU) is an experimental data product that provides information on employment and payroll dynamics for each quarter of the year at businesses that operate in one physical location. This paper describes the creation of the data tables and the value they add to the existing Business Dynamics Statistics (BDS) product. We then present some analysis of the published statistics to provide context for the numbers and demonstrate how they can be used to understand both national and local business conditions, with a particular focus on 2020 and the recession induced by the COVID-19 pandemic. We next examine how firms fared in this recession compared to the Great Recession that began in the fourth quarter of 2007. We also consider the heterogenous impact of the pandemic on various industries and areas of the country, showing which types of businesses in which locations were particularly hard hit. We examine business exit rates in some detail and consider why different metro areas experienced the pandemic in different ways. We also consider entry rates and look for evidence of a surge in new businesses as seen in other data sources. We finish by providing a preview of on-going research to match the BDS to worker demographics and show statistics on the relationship between the characteristics of the firm's workers and outcomes such as firm exit and net job creation.
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Small Business Growth and Failure during the Great Recession: The Role of House Prices, Race & Gender
November 2016
Working Paper Number:
carra-2016-08
Using 2002-2011 data from the Longitudinal Business Database linked to the 2002 and 2007 Survey of Business Owners, this paper explores whether (through a collateral channel) the rise in home prices over the early 2000's and their subsequent fall associated with the Great Recession had differential impacts on business performance across owner race, ethnicity and gender. We find that the employment growth rate of minority-owned firms, particularly black and Hispanic-owned firms, is more sensitive to changes in house prices than is that of their nonminority-owned counterparts.
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U.S. Long-Term Earnings Outcomes by Sex, Race, Ethnicity, and Place of Birth
May 2021
Working Paper Number:
CES-21-07R
This paper is part of the Global Income Dynamics Project cross-country comparison of earnings inequality, volatility, and mobility. Using data from the U.S. Census Bureau's Longitudinal Employer-Household Dynamics (LEHD) infrastructure files we produce a uniform set of earnings statistics for the U.S. From 1998 to 2019, we find U.S. earnings inequality has increased and volatility has decreased. The combination of increased inequality and reduced volatility suggest earnings growth differs substantially across different demographic groups. We explore this further by estimating 12-year average earnings for a single cohort of age 25-54 eligible workers. Differences in labor supply (hours paid and quarters worked) are found to explain almost 90% of the variation in worker earnings, although even after controlling for labor supply substantial earnings differences across demographic groups remain unexplained. Using a quantile regression approach, we estimate counterfactual earnings distributions for each demographic group. We find that at the bottom of the earnings distribution differences in characteristics such as hours paid, geographic division, industry, and education explain almost all the earnings gap, however above the median the contribution of the differences in the returns to characteristics becomes the dominant component.
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The Shifting Job Tenure Distribution
January 2016
Working Paper Number:
CES-16-12R
There has been a shift in the U.S. job tenure distribution toward longer-duration jobs since 2000. This change is apparent both in the tenure supplements to the Current Population Survey and in matched employer-employee data. A substantial portion of this shift can be accounted for by the ageing of the workforce and the decline in the entry rate of new employer businesses. This shift is accounted for more by declines in the hiring rate, which are concentrated in the labor market downturns associated with the 2001 and 2007-2009 recessions, rather than declines in separation rates. The increase in average real earnings since 2007 is less than what would be predicted by the shift toward longer-tenure jobs because of declines in tenure-held-constant real earnings. Regression estimates of the returns to job tenure provide no evidence that the shift in the job tenure distribution is being driven by better matches between workers and employers.
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Successor/Predecessor Firms
March 2002
Working Paper Number:
tp-2002-04
The goal of this research was to investigate the value added from using worker flows to identify the spurious births and deaths of businesses. We identify four types of "at risk" businesses from ES202 using the successor/predecessor flag and mimic the same categories using UI wage record data. We use two critical decision rules in the analysis: a successor firm has to have at least 80% of employment coming from the donor firm and (in two of the four categories) at least 5 employees have to come from the donor firm. We examine the sensitivity of the categories based on the percentage definition, and find that the results stay very similar, with the exception of the identification of the pure successor. We examine the sensitivity based on the count threshold, and find that there are enormous differences, particularly with identifying spinoff businesses.
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