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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Measuring the Business Dynamics of Firms that Received Pandemic Relief Funding: Findings from a New Experimental BDS Data Product
January 2025
Working Paper Number:
CES-25-05
This paper describes a new experimental data product from the U.S. Census Bureau's Center for Economic Studies: the Business Dynamics Statistics (BDS) of firms that received Small Business Administration (SBA) pandemic funding. This new product, BDS-SBA COVID, expands the set of currently published BDS tables by linking loan-level program participation data from SBA to internal business microdata at the U.S. Census Bureau. The linked programs include the Paycheck Protection Program (PPP), COVID Economic Injury Disaster Loans (COVID-EIDL), the Restaurant Revitalization Fund (RRF), and Shuttered Venue Operators Grants (SVOG). Using these linked data, we tabulate annual firm and establishment counts, measures of job creation and destruction, and establishment entry and exit for recipients and non-recipients of program funds in 2020-2021. We further stratify the tables by timing of loan receipt and loan size, and business characteristics including geography, industry sector, firm size, and firm age. We find that for the youngest firms that received PPP, the timing of receipt mattered. Receiving an early loan correlated with a lower job destruction rate compared to non-recipients and businesses that received a later loan. For the smallest firms, simply participating in PPP was associated with lower employment loss. The timing of PPP receipt was also related to establishment exit rates. For businesses of nearly all ages, those that received an early loan exited at a lower rate in 2022 than later loan recipients.
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Business Dynamics Statistics of Coastal Counties: A Description of Differences in Coastal Areas Over Time
January 2025
Working Paper Number:
CES-25-08R
The Business Dynamics Statistics of Coastal Counties (BDS-CC) is a new experimental data product extending the set of statistics published by the Business Dynamics Statistics (BDS) program to provide more detail on businesses operating in coastal regions of the United States. The BDS-CC provides annual measures of employment, the number of establishments and firms, job creation, job destruction, openings, and closings for businesses in Coastal Shoreline (CS), Coastal Non-Shoreline (CNS), and Non-Coastal (NC) counties. Counties are grouped into these categories based on definitions from the National Oceanic and Atmospheric Administration (NOAA). This product allows for comparisons across industries and coastal regions of the impact of natural disasters and other events that affect coastal areas. The BDS-CC series provides annual statistics for 1978 to 2022 for each of the coastal categories by firm size and firm age, initial firm size, establishment size and establishment age, initial establishment size, sector, 3-digit NAICS code, 4-digit NAICS code, urban/rural categories, and various coastal regions. Following a description of the data and methodology, we highlight some historical trends and analyses conducted using these 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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Business Formation: A Tale of Two Recessions
January 2021
Working Paper Number:
CES-21-01
The trajectory of new business applications and transitions to employer businesses differ markedly during the Great Recession and COVID-19 Recession. Both applications and transitions to employer startups decreased slowly but persistently in the post-Lehman crisis period of the Great Recession. In contrast, during the COVID-19 Recession new applications initially declined but have since sharply rebounded, resulting in a surge in applications during 2020. Projected transitions to employer businesses also rise but this is dampened by a change in the composition of applications in 2020 towards applications that are more likely to be nonemployers.
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Food and Agricultural Industries: Opportunities
for Improving Measurement and Reporting
January 2016
Working Paper Number:
CES-16-58
We measure one component of off-farm food and agricultural industries using establishment
level microdata in the federal statistical system. We focus on services for crop production, and compare measures of firm and employment dynamics in this sector during the period 1992-2012 with county-level publicly available data for the same measures. Based on differences across data sources, we establish new facts regarding the evolution of food and agricultural industries, and demonstrate the value of working with confidential microdata. In addition to the data and results we present, we highlight possibilities for collaboration across universities and federal agencies to improve reporting in other segments of food and agricultural industries.
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The Composition of Firm Workforces from 2006'2022: Findings from the Business Dynamics Statistics of Human Capital Experimental Product
April 2025
Working Paper Number:
CES-25-20
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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Older and Slower: The Startup Deficit's Lasting Effects on Aggregate Productivity Growth
June 2018
Working Paper Number:
CES-18-29
We investigate the link between declining firm entry, aging incumbent firms and sluggish U.S. productivity growth. We provide a dynamic decomposition framework to characterize the contributions to industry productivity growth across the firm age distribution and apply this framework to the newly developed Revenue-enhanced Longitudinal Business Database (ReLBD). Overall, several key findings emerge: (i) the relationship between firm age and productivity growth is downward sloping and convex; (ii) the magnitudes are substantial and significant but fade quickly, with nearly 2/3 of the effect disappearing after five years and nearly the entire effect disappearing after ten; (iii) the higher productivity growth of young firms is driven nearly exclusively by the forces of selection and reallocation. Our results suggest a cumulative drag on aggregate productivity of 3.1% since 1980. Using an instrumental variables strategy we find a consistent pattern across states/MSAs in the U.S. The patterns are broadly consistent with a standard model of firm dynamics with monopolistic competition.
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Early-Stage Business Formation: An Analysis of Applications for Employer Identification Numbers
December 2018
Working Paper Number:
CES-18-52
This paper reports on the development and analysis of a newly constructed dataset on the early stages of business formation. The data are based on applications for Employer Identification Numbers (EINs) submitted in the United States, known as IRS Form SS-4 filings. The goal of the research is to develop high-frequency indicators of business formation at the national, state, and local levels. The analysis indicates that EIN applications provide forward-looking and very timely information on business formation. The signal of business formation provided by counts of applications is improved by using the characteristics of the applications to model the likelihood that applicants become employer businesses. The results also suggest that EIN applications are related to economic activity at the local level. For example, application activity is higher in counties that experienced higher employment growth since the end of the Great Recession, and application counts grew more rapidly in counties engaged in shale oil and gas extraction. Finally, the paper provides a description of new public-use dataset, the 'Business Formation Statistics (BFS),' that contains new data series on business applications and formation. The initial release of the BFS shows that the number of business applications in the 3rd quarter of 2017 that have relatively high likelihood of becoming job creators is still far below pre-Great Recession levels.
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National Estimates of Gross Employment and Job Flows from the Quarterly Workforce Indicators with Demographic and Industry Detail
June 2010
Working Paper Number:
CES-10-11
The Quarterly Workforce Indicators (QWI) are local labor market data produced and released every quarter by the United States Census Bureau. Unlike any other local labor market series produced in the U.S. or the rest of the world, the QWI measure employment flows for workers (accession and separations), jobs (creations and destructions) and earnings for demographic subgroups (age and gender), economic industry (NAICS industry groups), detailed geography (block (experimental), county, Core- Based Statistical Area, and Workforce Investment Area), and ownership (private, all) with fully interacted publication tables. The current QWI data cover 47 states, about 98% of the private workforce in those states, and about 92% of all private employment in the entire economy. State participation is sufficiently extensive to permit us to present the first national estimates constructed from these data. We focus on worker, job, and excess (churning) reallocation rates, rather than on levels of the basic variables. This permits comparison to existing series from the Job Openings and Labor Turnover Survey and the Business Employment Dynamics Series from the Bureau of Labor Statistics. The national estimates from the QWI are an important enhancement to existing series because they include demographic and industry detail for both worker and job flow data compiled from underlying micro-data that have been integrated at the job and establishment levels by the Longitudinal Employer-Household Dynamics Program at the Census Bureau. The estimates presented herein were compiled exclusively from public-use data series and are available for download.
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Confidentiality Protection in the Census Bureau Quarterly Workforce Indicators
February 2006
Working Paper Number:
tp-2006-02
The QuarterlyWorkforce Indicators are new estimates developed by the Census Bureau's Longitudinal
Employer-Household Dynamics Program as a part of its Local Employment Dynamics
partnership with 37 state Labor Market Information offices. These data provide detailed quarterly
statistics on employment, accessions, layoffs, hires, separations, full-quarter employment
(and related flows), job creations, job destructions, and earnings (for flow and stock categories of
workers). The data are released for NAICS industries (and 4-digit SICs) at the county, workforce
investment board, and metropolitan area levels of geography. The confidential microdata - unemployment
insurance wage records, ES-202 establishment employment, and Title 13 demographic
and economic information - are protected using a permanent multiplicative noise distortion factor.
This factor distorts all input sums, counts, differences and ratios. The released statistics are analytically
valid - measures are unbiased and time series properties are preserved. The confidentiality
protection is manifested in the release of some statistics that are flagged as "significantly distorted
to preserve confidentiality." These statistics differ from the undistorted statistics by a significant
proportion. Even for the significantly distorted statistics, the data remain analytically valid for
time series properties. The released data can be aggregated; however, published aggregates are
less distorted than custom postrelease aggregates. In addition to the multiplicative noise distortion,
confidentiality protection is provided by the estimation process for the QWIs, which multiply imputes
all missing data (including missing establishment, given UI account, in the UI wage record
data) and dynamically re-weights the establishment data to provide state-level comparability with
the BLS's Quarterly Census of Employment and Wages.
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