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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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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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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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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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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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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Abandoning the Sinking Ship: The Composition of Worker Flows Prior to Displacement
August 2002
Working Paper Number:
tp-2002-11
declines experienced by workers several years before displacement occurs. Little attention, however,
has been paid to other changes in compensation and employment in firms prior to the actual
displacement event. This paper examines changes in the composition of job and worker flows
before displacement, and compares the "quality" distribution of workers leaving distressed firms to
that of all movers in general.
More specifically, we exploit a unique dataset that contains observations on all workers over
an extended period of time in a number of US states, combined with survey data, to decompose
different jobflow statistics according to skill group and number of periods before displacement.
Furthermore, we use quantile regression techniques to analyze changes in the skill profile of workers
leaving distressed firms. Throughout the paper, our measure for worker skill is derived from
person fixed effects estimated using the wage regression techniques pioneered by Abowd, Kramarz,
and Margolis (1999) in conjunction with the standard specification for displaced worker studies
(Jacobson, LaLonde, and Sullivan 1993).
We find that there are significant changes to all measures of job and worker flows prior to
displacement. In particular, churning rates increase for all skill groups, but retention rates drop
for high-skilled workers. The quantile regressions reveal a right-shift in the distribution of worker
quality at the time of displacement as compared to average firm exit flows. In the periods prior
to displacement, the patterns are consistent with both discouraged high-skilled workers leaving the
firm, and management actions to layoff low-skilled workers.
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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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High Frequency Business Dynamics in the United States During the COVID-19 Pandemic
March 2021
Working Paper Number:
CES-21-06
Existing small businesses experienced very sharp declines in activity, business sentiment, and expectations early in the pandemic. While there has been some recovery since the early days of the pandemic, small businesses continued to exhibit indicators of negative growth, business sentiment, and expectations through the first week of January 2021. These findings are from a unique high frequency, real time survey of small employer businesses, the Census Bureau's Small Business Pulse Survey (SBPS). Findings from the SBPS show substantial variation across sectors in the outcomes for small businesses. Small businesses in Accommodation and Food Services have been hit especially hard relative to those Finance and Insurance. However, even in Finance and Insurance small businesses exhibit indicators of negative growth, business sentiment, and expectations for all weeks from late April 2020 through the first week of 2021. While existing small businesses have fared poorly, after an initial decline, there has been a surge in new business applications based on the high frequency, real time Business Formation Statistics (BFS). Most of these applications are for likely nonemployers that are out of scope for the SBPS. However, there has also been a surge in new applications for likely employers. The surge in applications has been especially apparent in Retail Trade (and especially Non-store Retailers). We compare and contrast the patterns from these two new high frequency data products that provide novel insights into the distinct patterns of dynamics for existing small businesses relative to new business formations.
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